Libraries Needed

library(factoextra)
## Warning: package 'factoextra' was built under R version 4.3.3
## Loading required package: ggplot2
## Welcome! Want to learn more? See two factoextra-related books at https://goo.gl/ve3WBa
library(dplyr)
## 
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union
library(data.table)
## 
## Attaching package: 'data.table'
## The following objects are masked from 'package:dplyr':
## 
##     between, first, last
library(ggplot2)
library(maps)
## Warning: package 'maps' was built under R version 4.3.3

Loading & Subsetting Data

#EJI Data
eji = read.csv("C:/Users/Katie/Desktop/EJI.csv")
eji_ny = eji[which(eji$StateDesc == 'New York'),]
eji_ny = eji_ny[which(eji_ny$COUNTY == 'New York' | eji_ny$COUNTY == "Bronx" | eji_ny$COUNTY == "Kings" | eji_ny$COUNTY == "Queens"), ]
#PM2.5 Data
pops_2.5_walk1 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk1.csv") #ny 
pops_2.5_walk1$walk = 1

pops_2.5_walk2 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk2.csv") #ny
pops_2.5_walk2$walk = 2

pops_2.5_walk3 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk3.csv") #ny
pops_2.5_walk3$walk = 3

pops_2.5_walk4 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk4.csv") #ny
pops_2.5_walk4$walk = 4

pops_2.5_walk5 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk5.csv") #ny
pops_2.5_walk5$walk = 5

pops_2.5_walk6 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk6.csv") #ny
pops_2.5_walk6$walk = 6

pops_2.5_walk7 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk7.csv") #ny
pops_2.5_walk7$walk = 7

pops_2.5_walk8 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk8.csv") #ny
pops_2.5_walk8$walk = 8

pops_2.5_walk9 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk9.csv") #ny/kings
pops_2.5_walk9$walk = 9

pops_2.5_walk10 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk10.csv") #ny
pops_2.5_walk10$walk = 10

pops_2.5_walk11 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk11.csv") #ny
pops_2.5_walk11$walk = 11

pops_2.5_walk12 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk12.csv") #ny
pops_2.5_walk12$walk = 12

pops_2.5_walk13 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk13.csv") #ny
pops_2.5_walk13$walk = 13

pops_2.5_walk14 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk14.csv") #ny
pops_2.5_walk14$walk = 14

pops_2.5_walk15 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk15.csv") #ny
pops_2.5_walk15$walk = 15

pops_2.5_walk16 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk16.csv") #kings
pops_2.5_walk16$walk = 16

pops_2.5_walk17 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk17.csv") #kings
pops_2.5_walk17$walk = 17

pops_2.5_walk18 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk18.csv") #ny/bronx
pops_2.5_walk18$walk = 18

pops_2.5_walk19 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk19.csv") #ny/bronx
pops_2.5_walk19$walk = 19

pops_2.5_walk20 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk20.csv") #ny/bronx
pops_2.5_walk20$walk = 20

pops_2.5_walk21 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk21.csv") #ny
pops_2.5_walk21$walk = 21

pops_2.5_walk22 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk22.csv") #ny
pops_2.5_walk22$walk = 22

pops_2.5_walk23 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk23.csv") #ny
pops_2.5_walk23$walk = 23

pops_2.5_walk24 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk24.csv") #ny
pops_2.5_walk24$walk = 24

pops_2.5_walk25 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk25.csv") #ny
pops_2.5_walk25$walk = 25

pops_2.5_walk26 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk26.csv") #ny
pops_2.5_walk26$walk = 26

pops_2.5_allwalks = rbind(pops_2.5_walk1,pops_2.5_walk2, pops_2.5_walk3, pops_2.5_walk4, pops_2.5_walk5, pops_2.5_walk6, pops_2.5_walk7, pops_2.5_walk8, pops_2.5_walk9, pops_2.5_walk10, pops_2.5_walk11, pops_2.5_walk12, pops_2.5_walk13, pops_2.5_walk14, pops_2.5_walk15, pops_2.5_walk16, pops_2.5_walk17, pops_2.5_walk18, pops_2.5_walk19, pops_2.5_walk20, pops_2.5_walk21, pops_2.5_walk22, pops_2.5_walk23, pops_2.5_walk24, pops_2.5_walk25, pops_2.5_walk26)

allwalks = pops_2.5_allwalks[which(pops_2.5_allwalks$TimeUTC != "NaT"), ]
  
allwalks$COUNTY = ifelse(allwalks$walk >= 1 & allwalks$walk <= 15, "New York",
                   ifelse(allwalks$walk >= 16 & allwalks$walk <= 17, "Kings",
                   ifelse(allwalks$walk >= 18 & allwalks$walk <= 26, "New York", "Pending")))

allwalks[5535:5831, 13] = "Kings" #walk 9
allwalks[11584:11681, 13] = "Bronx" #walk 18
allwalks[11897:12215, 13] = "Bronx" #walk 19
allwalks[12392:12829, 13] = "Bronx" #walk 20


allwalks_base = allwalks %>%
  select(TimeUTC, PM25_POPS, walk, COUNTY)

Variables of Interest

  1. Name of Census Tract

  2. E_TOTPOP # estimated total population from 2014-2018

  3. E_OZONE # annual mean days above O3 regulatory standard (3-year average)

  4. E_PM # annual mean days above PM2.5 regulatory standards (3-year average)

  5. E_PARK #proportion of census tract’s area within 1 mi buffer of green space

  6. E_AIRPORT #proportion of census tract’s area within 1 mi buffer of airport

  7. E_TOTCR #probability of contracting cancer over the course of a lifetime assuming continous exposure

  8. RPL_EJI # EJI rank

  9. RPL_EBM # environmental burden rank

  10. RPL_SVM # social vulnerability module rank

  11. RPL_HVM # percentile rank of combined tertile (health risks) flags

  12. EP_MINRTY # percentage of minority persons

  13. EP_POV200 # percentage below 200% poverty

  14. EP_CANCER # percentage of individuals with cancer

  15. EP_ASTHMA # percentage of individuals with asthma

  16. EP_LIMENG # percentage of persons (5+) who speak English “less than well”

  17. EP_DISABL # percentage of persons who are disabled

  18. EP_AGE65 # percentage of persons aged 65 and older

  19. EP_UNINSUR # percentage or persons uninsured

  20. EP_UNEMP # percentage of persons with no high school diploma (25+)

Base Model

  1. Name of Census Tract (index column)
  2. E_PM # annual mean days above PM2.5 regulatory standards (3-year average)
  3. E_TOTCR # probability of contracting cancer over the course of a lifetime assuming continuous exposure
  4. EP_MINRTY # percentage of minority persons
  5. RPL_EJI # EJI rank
  6. RPL_SVM # social vulnerability module rank
  7. E_TOTPOP # estimated total population from 2014-2018

Base Model

Exploratory Analysis

EJI Box Plots & Summary Statistics

#Base Model Variables
eji_base = eji_ny %>%
  select(NAME, COUNTY, E_PM, E_TOTCR, EP_MINRTY, RPL_EJI, RPL_SVM, E_TOTPOP)

#Summary Statistics
eji_base %>%
  group_by(COUNTY) %>%
  summarise(median_min = median(EP_MINRTY), mean_min = mean(EP_MINRTY))
#Categorizing majority "minority" counties
  #This is based on the average % of minorities in each county
eji_base$minority = ifelse(eji_base$EP_MINRTY >= 87 & eji_base$COUNTY == "Bronx", "minority", 
                    ifelse(eji_base$EP_MINRTY >= 62 & eji_base$COUNTY == "Kings", "minority",
                    ifelse(eji_base$EP_MINRTY >= 51 & eji_base$COUNTY == "New York", "minority",
                    ifelse(eji_base$EP_MINRTY >= 72 & eji_base$COUNTY == "Queens", "minority", "non-minority"))))

#Box plot of NY Counties and Rank of EJI 
  #Minority counties def have a higher EJI rank than non-minority counties
  #New York county has the biggest disparity
ggplot(eji_base, aes(x= COUNTY, y=RPL_EJI, fill = minority)) + 
    geom_boxplot() +
    coord_flip() +
    scale_fill_manual(values = c("darkseagreen", "burlywood3")) +
    #geom_jitter(position = position_jitter(0.15)) +
    theme_classic() +
    labs(x = "New York Counties", y = "Rank of EJI")
## Warning: Removed 59 rows containing non-finite values (`stat_boxplot()`).

#Box plot of NY counties vs Above Pm2.5 Regulatory Standards
  #There is not a substantial difference between minority and non-minority counties. 
  #Queens does have the largest spread.
ggplot(eji_base, aes(x= COUNTY, y=E_PM, fill = minority)) + 
    geom_boxplot() +
    coord_flip() +
    scale_fill_manual(values = c("darkseagreen", "burlywood3")) +
    #geom_jitter(position = position_jitter(0.15)) +
    theme_classic() +
    labs(x = "New York Counties", y = "Annaul Mean Days Above PM2.5 Regulatory Standards")
## Warning: Removed 2 rows containing non-finite values (`stat_boxplot()`).

#Box plot of NY counties vs Social Vulnerability Rank
  #Minority counties have a higher social vulnerability rank than non-minority counties
  #Kings and Queens have the largest spread
  #New York has the biggest difference between non-minority and minortiy counties
ggplot(eji_base, aes(x= COUNTY, y=RPL_SVM, fill = minority)) + 
    geom_boxplot() +
    coord_flip() +
    scale_fill_manual(values = c("darkseagreen", "burlywood3")) +
    #geom_jitter(position = position_jitter(0.15)) +
    theme_classic() +
    labs(x = "New York Counties", y = "Social Vulnerability Rank")
## Warning: Removed 50 rows containing non-finite values (`stat_boxplot()`).

Histograms of CDC vs Backpack Campaign

CDC

#Loading in CDC estimated daily concentration levels for PM2.5 
  #Am only using 2016 - Aug and July - for a direct comparison to Backpack campaign
  #Also only looking at the four new york counties of interest
  #EJI uses these predicted values from 2014-2016
CDC_PM25 = read.csv("C:/Users/Katie/Desktop/CDC Daily Concentration Levels.csv")
CDC_PM25_sub = CDC_PM25[which((CDC_PM25$countyfips == 5 | CDC_PM25$countyfips == 61 | CDC_PM25$countyfips == 47 | CDC_PM25$countyfips == 81) & CDC_PM25$year == 2016), ]

#Renaming the counties 
CDC_PM25_sub$county = ifelse(CDC_PM25_sub$countyfips == 5, "Bronx",
                      ifelse(CDC_PM25_sub$countyfips == 47, "Kings",
                      ifelse(CDC_PM25_sub$countyfips == 61, "New York", "Queens")))

#Changing county variable to factor
CDC_PM25_sub$county = as.factor(CDC_PM25_sub$county)

#Histogram of CDC estimated PM2.5 for these coutnies 
  #For July & Aug of 2016 the range for the daily PM2.5 is about 0 to 20 for each county
ggplot(CDC_PM25_sub, aes(x=PM25_pop_pred, fill = county)) +
  geom_histogram( color="#e9ecef", alpha=0.6, position = 'identity') +
  facet_wrap(~county) +
  xlab("Predicted PM2.5 Concentration Levels") +
  ylab("Frequency of PM2.5 Levels")
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

summary(CDC_PM25_sub$PM25_pop_pred)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   3.209   6.899   9.065   9.258  11.195  17.481
#Min = 3.209, #Median = 9.065, #Max = 17.481

Backpacking Campaign

#Creating a day variable from the TimeUTC var. 
  #Removing some outliers for more easy comparison
allwalks_base$day = sub("^\\d+/([0-9]+)/\\d+.*", "\\1", allwalks_base$TimeUTC)
allwalks_base = allwalks_base[which(allwalks_base$PM25_POPS <= 150), ]

#Histogram of Backpacking PM2.5 by county
  #This is not an average by the PM2.5 seen every 15 minutes for each walk
  #The range here is much higher than CDC.
  #We are seeing much higher levels of PM2.5
ggplot(allwalks_base, aes(x=PM25_POPS, fill = COUNTY)) +
  geom_histogram( color="#e9ecef", alpha=0.6, position = 'identity') +
  facet_wrap(~COUNTY) +
  xlab("Backpack Campaign Concentration Levels") +
  ylab("Frequency of PM2.5 Levels")
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

#Averaging the PM2.5 by day 
allwalks_base_grouped = allwalks_base %>%
  group_by(day, COUNTY) %>%
  summarise(PM25_avg = mean(PM25_POPS, na.rm = TRUE))
## `summarise()` has grouped output by 'day'. You can override using the `.groups`
## argument.
#Histogram of the backpacking campaign of the average PM2.5 per day by county
  #Still averaging it shows that there are higher reading for PM2.5 compared to CDC predicted 
ggplot(allwalks_base_grouped, aes(x=PM25_avg, fill = COUNTY)) +
  geom_histogram(color="#e9ecef", alpha=0.6, position = 'identity') +
  facet_wrap(~COUNTY) +
  xlab("Backpack Campaign Concentration Levels") +
  ylab("Frequency of PM2.5 Levels")
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

summary(allwalks_base$PM25_POPS)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   1.382   9.117  15.733  19.295  28.898 148.109
#Min = 1.382, Median = 15.778, #3rd Quartile = 29.050 #Max = 423

Bronx clustering analysis

Base Model

Training Data

eji_base_bronx = eji_base[which(eji_base$COUNTY == 'Bronx'),]
eji_base_bronx = na.omit(eji_base_bronx)

#Finding what variables to use from base model

library(caret)
## Warning: package 'caret' was built under R version 4.3.3
## Loading required package: lattice
correlation_matrix = cor(eji_base_bronx[, c(3:8)]) #EP_MINRTY, RPL_SVM, RPL_EJI

# Setting seed 
set.seed(123)

train_sample = sample(seq_len(nrow(eji_base_bronx)), size = 231)
train = eji_base_bronx[train_sample, ]
test = eji_base_bronx[-train_sample, ]

# Training data
# Normalizing the data

z = train[, c(5:7)]
means = apply(z, 2, mean)
sds = apply(z, 2, sd)
nor = scale(z, center = means, scale = sds) 

# How many clusters? 
fviz_nbclust(nor, kmeans, method = "silhouette") # 2 clusters

# K Means on 2 Clusters
kmeans_result = kmeans(nor, centers = 2)  # default gives 61.5%
kmeans_result 
## K-means clustering with 2 clusters of sizes 189, 42
## 
## Cluster means:
##    EP_MINRTY   RPL_EJI    RPL_SVM
## 1  0.3914532  0.368285  0.3479536
## 2 -1.7615394 -1.657283 -1.5657912
## 
## Clustering vector:
## 42807 42638 42823 42935 42745 42928 42858 42873 42959 42780 42715 42716 42885 
##     1     1     2     1     1     1     1     1     1     1     2     1     1 
## 42825 42949 42764 42650 42631 42944 42883 42839 42703 42706 42667 42770 42656 
##     1     2     1     1     1     1     1     2     1     1     1     1     1 
## 42736 42892 42647 42762 42853 42793 42845 42919 42694 42697 42701 42688 42768 
##     1     1     1     1     2     1     2     1     1     2     1     1     1 
## 42838 42951 42906 42665 42950 42852 42640 42743 42719 42891 42864 42711 42663 
##     2     2     1     1     2     1     1     1     1     1     1     2     1 
## 42786 42869 42837 42658 42627 42637 42925 42872 42714 42649 42907 42748 42737 
##     1     2     2     1     1     1     1     1     1     1     1     1     2 
## 42785 42689 42827 42692 42778 42710 42792 42763 42675 42699 42806 42733 42865 
##     1     2     2     1     1     1     1     1     1     2     2     1     2 
## 42724 42948 42842 42754 42832 42840 42801 42641 42818 42670 42678 42790 42861 
##     1     1     1     1     2     2     1     1     1     1     1     1     2 
## 42895 42912 42704 42648 42740 42843 42734 42930 42849 42835 42890 42781 42729 
##     1     1     1     1     1     2     1     1     2     2     1     1     1 
## 42787 42918 42782 42797 42628 42695 42914 42882 42934 42645 42679 42700 42791 
##     1     1     1     2     1     1     1     1     1     1     1     1     1 
## 42708 42908 42871 42941 42932 42672 42702 42841 42812 42738 42876 42824 42624 
##     1     1     1     1     1     1     2     2     2     1     1     1     1 
## 42795 42654 42867 42848 42713 42939 42804 42644 42731 42718 42879 42676 42735 
##     1     1     2     2     1     1     2     1     1     1     1     2     1 
## 42646 42805 42666 42683 42709 42635 42896 42887 42900 42889 42933 42862 42859 
##     1     1     1     1     1     1     1     1     1     1     1     1     2 
## 42875 42799 42855 42660 42769 42947 42752 42657 42664 42634 42828 42633 42942 
##     1     1     1     1     1     1     1     1     1     1     1     1     1 
## 42854 42685 42779 42922 42958 42954 42943 42794 42742 42888 42677 42784 42822 
##     1     1     1     1     1     1     1     1     1     1     1     1     2 
## 42810 42898 42817 42929 42788 42916 42681 42732 42728 42931 42952 42868 42761 
##     1     1     2     1     1     1     1     1     1     1     2     1     1 
## 42946 42756 42940 42910 42937 42653 42772 42651 42884 42789 42684 42744 42808 
##     1     1     1     2     1     1     1     1     1     1     1     1     2 
## 42917 42811 42629 42741 42826 42655 42819 42874 42893 42661 42915 42821 42659 
##     1     1     1     1     1     1     1     1     1     1     1     1     1 
## 42899 42857 42691 42903 42880 42723 42851 42774 42632 42844 
##     1     1     1     1     1     2     2     1     1     2 
## 
## Within cluster sum of squares by cluster:
## [1] 136.4363 127.4299
##  (between_SS / total_SS =  61.8 %)
## 
## Available components:
## 
## [1] "cluster"      "centers"      "totss"        "withinss"     "tot.withinss"
## [6] "betweenss"    "size"         "iter"         "ifault"
# Plot of Cluster
fviz_cluster(kmeans_result, data = nor)

# Silhouette coefficient
library(cluster)
## 
## Attaching package: 'cluster'
## The following object is masked from 'package:maps':
## 
##     votes.repub
sil = as.data.frame(silhouette(kmeans_result$cluster, dist(nor)))
mean(sil$sil_width) # 0.66 <- could potentially have a better algorithm
## [1] 0.6552715
fviz_silhouette(silhouette(kmeans_result$cluster, dist(nor)))
##   cluster size ave.sil.width
## 1       1  189          0.72
## 2       2   42          0.36

# Adding Clusters to data set
train = train %>% 
  mutate(km.group = factor(kmeans_result$cluster, labels=c("cl1","cl2"))) 

# Summarizing the cluster groups
train %>%
  group_by(km.group) %>%
  summarise(count = n(),
            E_PM = mean(E_PM),
            RPL_EJI = mean(RPL_EJI),
            RPL_SVM = mean(RPL_SVM))
# 75% are in cluster 2 (higher ratings) <- minorities
# 25% are in cluster 1 (lower ratings) <- non-minorities

table(train$km.group, train$minority)
##      
##       minority non-minority
##   cl1      174           15
##   cl2        4           38
# cluster two has 75% of minority groups

# Are there significant differences?

aov_test = aov(RPL_EJI ~ km.group, data = train)
summary(aov_test) #yes there are significant differences 
##              Df Sum Sq Mean Sq F value Pr(>F)    
## km.group      1  2.491  2.4911   362.7 <2e-16 ***
## Residuals   229  1.573  0.0069                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
aov_test = aov(RPL_SVM ~ km.group, data = train)
summary(aov_test) #yes there are significant differences 
##              Df Sum Sq Mean Sq F value Pr(>F)    
## km.group      1  3.918   3.918   276.7 <2e-16 ***
## Residuals   229  3.242   0.014                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
aov_test = aov(E_PM ~ km.group, data = train)
summary(aov_test) #yes there are significant differences
##              Df Sum Sq  Mean Sq F value  Pr(>F)   
## km.group      1 0.0197 0.019698   7.243 0.00764 **
## Residuals   229 0.6228 0.002719                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Testing Data

# Setting seed 
set.seed(123)

z = test[, c(5:7)]
means = apply(z, 2, mean)
sds = apply(z, 2, sd)
nor = scale(z, center = means, scale = sds) 

# How many clusters? 
fviz_nbclust(nor, kmeans, method = "silhouette") # 2 clusters

# K Means on 2 Clusters
kmeans_result = kmeans(nor, centers = 2)  # default gives 68.7%
kmeans_result 
## K-means clustering with 2 clusters of sizes 19, 80
## 
## Cluster means:
##    EP_MINRTY    RPL_EJI    RPL_SVM
## 1 -1.5919220 -1.7144558 -1.6815723
## 2  0.3780815  0.4071833  0.3993734
## 
## Clustering vector:
## 42625 42626 42636 42639 42642 42643 42652 42662 42668 42669 42671 42673 42674 
##     1     2     2     2     2     2     2     2     2     2     2     2     2 
## 42680 42682 42687 42690 42693 42696 42698 42705 42707 42712 42717 42721 42722 
##     2     2     2     2     2     2     2     2     2     2     1     1     2 
## 42725 42727 42730 42739 42746 42747 42749 42750 42751 42753 42755 42757 42758 
##     2     2     2     2     2     2     2     2     2     2     2     2     2 
## 42759 42760 42765 42766 42767 42771 42773 42775 42776 42777 42783 42796 42798 
##     2     2     2     2     2     2     1     2     2     2     2     2     2 
## 42800 42802 42809 42813 42814 42815 42816 42820 42829 42830 42831 42833 42834 
##     1     1     2     2     1     2     1     2     2     1     1     1     2 
## 42836 42846 42847 42856 42860 42863 42866 42870 42877 42878 42881 42886 42894 
##     1     1     1     2     2     2     2     1     2     2     2     2     2 
## 42897 42901 42902 42904 42905 42909 42911 42913 42920 42921 42923 42924 42926 
##     2     2     2     2     2     2     1     2     2     2     2     2     2 
## 42927 42936 42938 42953 42955 42956 42957 42961 
##     2     2     1     1     2     2     2     1 
## 
## Within cluster sum of squares by cluster:
## [1] 47.04045 51.77618
##  (between_SS / total_SS =  66.4 %)
## 
## Available components:
## 
## [1] "cluster"      "centers"      "totss"        "withinss"     "tot.withinss"
## [6] "betweenss"    "size"         "iter"         "ifault"
# Plot of Cluster
fviz_cluster(kmeans_result, data = nor)

# Silhouette coefficient
sil = as.data.frame(silhouette(kmeans_result$cluster, dist(nor)))
mean(sil$sil_width) # 0.68 <- could potentially have a better algorithm
## [1] 0.6776646
# all of cluster 1 remains under the average and has some negative values

fviz_silhouette(silhouette(kmeans_result$cluster, dist(nor)))
##   cluster size ave.sil.width
## 1       1   19          0.40
## 2       2   80          0.74

# Adding Clusters to data set
test = test %>% 
  mutate(km.group = factor(kmeans_result$cluster, labels=c("cl1","cl2"))) 

# Summarizing the cluster groups
test %>%
  group_by(km.group) %>%
  summarise(count = n(),
            E_PM = mean(E_PM),
            RPL_EJI = mean(RPL_EJI),
            RPL_SVM = mean(RPL_SVM))
# 88% are in cluster 1 (higher ratings) <- minorities
# 12% are in cluster 2 (lower ratings) <- non-minorities

table(test$km.group, test$minority)
##      
##       minority non-minority
##   cl1        3           16
##   cl2       75            5
# cluster 1 has 100% of minority groups

# Are there significant differences?

aov_test = aov(RPL_EJI ~ km.group, data = test)
summary(aov_test) #yes there are significant differences 
##             Df Sum Sq Mean Sq F value Pr(>F)    
## km.group     1 1.1116  1.1116   232.1 <2e-16 ***
## Residuals   97 0.4647  0.0048                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
aov_test = aov(RPL_SVM ~ km.group, data = test)
summary(aov_test) #yes there are significant differences 
##             Df Sum Sq Mean Sq F value Pr(>F)    
## km.group     1 1.7002  1.7002   204.6 <2e-16 ***
## Residuals   97 0.8059  0.0083                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
aov_test = aov(E_PM ~ km.group, data = test)
summary(aov_test) #yes there are significant differences
##             Df  Sum Sq  Mean Sq F value  Pr(>F)   
## km.group     1 0.02081 0.020810   7.805 0.00628 **
## Residuals   97 0.25862 0.002666                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

More Complex Model

Training Data

eji_base_bronx = eji_ny[which(eji_base$COUNTY == 'Bronx'),]
eji_base_bronx = na.omit(eji_base_bronx)

#Finding what variables to use from base model
#Above 0.60
correlation_matrix = cor(eji_base_bronx[, c(11:118)])
## Warning in cor(eji_base_bronx[, c(11:118)]): the standard deviation is zero
correlation_matrix
##                    E_TOTPOP     M_TOTPOP     E_DAYPOP      SPL_EJI      RPL_EJI
## E_TOTPOP        1.000000000  0.913624562  0.536985177  0.236417590  0.220098142
## M_TOTPOP        0.913624562  1.000000000  0.489866799  0.275221724  0.266750288
## E_DAYPOP        0.536985177  0.489866799  1.000000000  0.117437390  0.105770495
## SPL_EJI         0.236417590  0.275221724  0.117437390  1.000000000  0.984167737
## RPL_EJI         0.220098142  0.266750288  0.105770495  0.984167737  1.000000000
## SPL_SER         0.236797420  0.266173527  0.159012269  0.867696259  0.872834600
## RPL_SER         0.209960783  0.244079073  0.135308331  0.849689863  0.877134806
## EPL_OZONE      -0.086152598 -0.040797106 -0.064443835 -0.428683733 -0.395576041
## EPL_PM          0.077664639  0.078420374 -0.018283228  0.219251524  0.259574129
## EPL_DSLPM       0.113751822  0.056234593  0.044114534  0.529618513  0.518134116
## EPL_TOTCR       0.094435056  0.052723751  0.098293532  0.541795393  0.526645043
## SPL_EBM_THEME1  0.038009262  0.041901746  0.015444647  0.186606723  0.227586894
## RPL_EBM_DOM1    0.033511201  0.039679649  0.013425224  0.164712720  0.207292926
## EPL_NPL                  NA           NA           NA           NA           NA
## EPL_TRI        -0.026527798 -0.063817597  0.048827533  0.279978463  0.263246293
## EPL_TSD        -0.027435750 -0.030298401  0.165740246 -0.014974058 -0.005130206
## EPL_RMP         0.053541072  0.070376395  0.187665717 -0.047129642 -0.027357417
## EPL_COAL                 NA           NA           NA           NA           NA
## EPL_LEAD                 NA           NA           NA           NA           NA
## SPL_EBM_THEME2  0.015747018 -0.006330987  0.227140161  0.227385803  0.229258930
## RPL_EBM_DOM2    0.031836776  0.003350790  0.192928315  0.245751889  0.248333400
## EPL_PARK        0.019553936  0.033953987  0.038519067 -0.221954214 -0.266994837
## EPL_HOUAGE      0.028027260 -0.003912778 -0.052436618 -0.170076081 -0.146944433
## EPL_WLKIND      0.268506365  0.271973165  0.059748723  0.155237321  0.132665235
## SPL_EBM_THEME3  0.167826777  0.146463230 -0.004873365 -0.058076270 -0.055605142
## RPL_EBM_DOM3    0.176313053  0.156045555 -0.004302228 -0.046663672 -0.043951243
## EPL_RAIL        0.070379914  0.066743492  0.044731298  0.419894579  0.493290595
## EPL_ROAD       -0.023038579 -0.075837118 -0.146697063  0.082928635  0.113157484
## EPL_AIRPRT     -0.009737170  0.027652409  0.331215926  0.076782106  0.062807797
## SPL_EBM_THEME4  0.046254624  0.044598774  0.154156026  0.414960061  0.478998831
## RPL_EBM_DOM4    0.051988494  0.045464679  0.099983777  0.419059170  0.488494966
## EPL_IMPWTR      0.038561491  0.052456103 -0.021906638  0.513525204  0.521641736
## SPL_EBM_THEME5  0.038561491  0.052456103 -0.021906638  0.513525204  0.521641736
## RPL_EBM_DOM5    0.038492890  0.052380312 -0.021988926  0.513531704  0.521661366
## SPL_EBM         0.108808769  0.084001096  0.215084797  0.341508796  0.368912381
## RPL_EBM         0.114522869  0.080443471  0.147715784  0.389062710  0.429100559
## EPL_MINRTY      0.214363665  0.262441712  0.017797712  0.707582693  0.711102717
## SPL_SVM_DOM1    0.214363665  0.262441712  0.017797712  0.707582693  0.711102717
## RPL_SVM_DOM1    0.214363665  0.262441712  0.017797712  0.707582693  0.711102717
## EPL_POV200      0.202090004  0.243440482  0.108402017  0.828979331  0.809151757
## EPL_NOHSDP      0.140459315  0.202449846  0.009897681  0.771515954  0.763078484
## EPL_UNEMP       0.138645725  0.176468974  0.097365607  0.464080469  0.440172547
## EPL_RENTER      0.224735903  0.247205073  0.155972046  0.679350497  0.672882894
## EPL_HOUBDN      0.072982701  0.153358948  0.012455246  0.695002091  0.714209929
## EPL_UNINSUR     0.175405402  0.220267541  0.052294103  0.419000606  0.433549379
## EPL_NOINT       0.134519359  0.164350897  0.064211504  0.649882575  0.613442157
## SPL_SVM_DOM2    0.207046198  0.264893943  0.097637151  0.833601585  0.820419046
## RPL_SVM_DOM2    0.197585538  0.262182685  0.090685237  0.825666288  0.823578049
## EPL_AGE65      -0.173335833 -0.200062762 -0.031674831 -0.477124765 -0.465894432
## EPL_AGE17       0.201259174  0.221374883 -0.018089749  0.576262009  0.548225297
## EPL_DISABL      0.005213395 -0.021609776  0.039906069  0.216310778  0.152617785
## EPL_LIMENG      0.173162374  0.158109944  0.045422018  0.500768878  0.491335408
## SPL_SVM_DOM3    0.087442846  0.062528891  0.001981533  0.382362295  0.329428704
## RPL_SVM_DOM3    0.121037732  0.095556369  0.014219920  0.381845605  0.334517415
## EPL_MOBILE     -0.058135856 -0.043297846 -0.024719933 -0.002016489 -0.008480951
## EPL_GROUPQ      0.162360961  0.142615154  0.246840201  0.216106241  0.202954638
## SPL_SVM_DOM4    0.111784461  0.101966066  0.200900154  0.185427617  0.170940510
## RPL_SVM_DOM4    0.090832819  0.076581011  0.209366213  0.171879389  0.158663847
## SPL_SVM         0.231338235  0.270346532  0.132577113  0.852225176  0.824308531
## RPL_SVM         0.229862195  0.279759981  0.122998437  0.855826212  0.844185135
## F_BPHIGH        0.029018882  0.056477775  0.003944683  0.448499138  0.404320683
## F_ASTHMA        0.189883947  0.245741313  0.055312509  0.741420046  0.768079805
## F_CANCER       -0.080458859 -0.148166148  0.024548769 -0.375328250 -0.360092986
## F_MHLTH         0.170660883  0.186228688  0.037223606  0.749225719  0.681200328
## F_DIABETES      0.194507961  0.256753711  0.050159952  0.808037101  0.822128705
## F_HVM           0.186490778  0.225262782  0.057041126  0.903994028  0.873446796
## RPL_HVM         0.186490778  0.225262782  0.057041126  0.903994028  0.873446796
## E_OZONE        -0.064491773 -0.024845942 -0.041035312 -0.461650686 -0.432473057
## E_PM            0.076745301  0.077646920 -0.017960560  0.232085644  0.273295934
## E_DSLPM         0.126101355  0.065142298  0.024253193  0.500719267  0.475082311
## E_TOTCR         0.093322977  0.052597208  0.102668101  0.548922049  0.520393571
## E_NPL                    NA           NA           NA           NA           NA
## E_TRI          -0.029465353 -0.058235484  0.049779838  0.299553805  0.280634702
## E_TSD          -0.027435750 -0.030298401  0.165740246 -0.014974058 -0.005130206
## E_RMP           0.084025890  0.107208668  0.152795958 -0.024655354 -0.005354821
## E_COAL                   NA           NA           NA           NA           NA
## E_LEAD                   NA           NA           NA           NA           NA
## E_PARK         -0.018091031 -0.036007141 -0.036973389  0.218104212  0.262178305
## E_HOUAGE        0.027762532 -0.002710476 -0.052177602 -0.159236163 -0.136864795
## E_WLKIND       -0.275150054 -0.275264854 -0.064151814 -0.161185819 -0.138309083
## E_RAIL          0.074087957  0.069866006  0.043575517  0.418816771  0.489642955
## E_ROAD         -0.019435221 -0.069885206 -0.160865578  0.057853631  0.085331807
## E_AIRPRT        0.034347987  0.077884929  0.423779728  0.056042715  0.048252223
## E_IMPWTR        0.019083813  0.040494363 -0.036460865  0.483355038  0.499451485
## EP_MINRTY       0.223953727  0.272221808  0.021597292  0.715317565  0.721970354
## EP_POV200       0.180564658  0.207334560  0.115987510  0.805142223  0.767671292
## EP_NOHSDP       0.142116110  0.181519595  0.011166800  0.755227207  0.714616067
## EP_UNEMP        0.108648338  0.119303604  0.070496684  0.449828229  0.416421286
## EP_RENTER       0.233875973  0.243624730  0.151737335  0.728646914  0.708230402
## EP_HOUBDN       0.049183523  0.089727934  0.039455670  0.639389119  0.639001419
## EP_UNINSUR      0.178761415  0.226720802  0.066084694  0.387141230  0.397788252
## EP_NOINT        0.090422389  0.121999506  0.043346061  0.625370322  0.578503713
## EP_AGE65       -0.160133244 -0.195020522  0.006000718 -0.421463367 -0.412061868
## EP_AGE17        0.182831447  0.195758963 -0.071169371  0.523835363  0.495913306
## EP_DISABL      -0.060611900 -0.070605168  0.088962968  0.181487960  0.126522377
## EP_LIMENG       0.173441610  0.159041731  0.001210396  0.512676896  0.500632794
## EP_MOBILE      -0.081225911 -0.060258416  0.008028264 -0.044919676 -0.051002492
## EP_GROUPQ      -0.107475004 -0.117557173  0.295105468 -0.040033128 -0.045044644
## EP_BPHIGH       0.090970931  0.120146853 -0.015970754  0.503024027  0.483819345
## EP_ASTHMA       0.138921307  0.185651234  0.013695233  0.763426251  0.726552279
## EP_CANCER      -0.144992129 -0.179400052 -0.068758742 -0.511763363 -0.504149055
## EP_MHLTH        0.144089277  0.177001850  0.058676900  0.799612382  0.753046367
## EP_DIABETES     0.131260675  0.159736786  0.024572290  0.802809887  0.758125195
## EPL_BPHIGH      0.084142056  0.115766854 -0.020776721  0.553117083  0.532787761
## EPL_ASTHMA      0.200286128  0.259854111  0.058861106  0.831539421  0.826436568
## EPL_CANCER     -0.143152608 -0.182268395 -0.041446714 -0.555457278 -0.547689410
## EPL_DIABETES    0.214146472  0.262310202  0.025061291  0.880001774  0.870364911
## EPL_MHLTH       0.168604433  0.213508039  0.067479328  0.849611389  0.807295449
##                    SPL_SER      RPL_SER     EPL_OZONE       EPL_PM    EPL_DSLPM
## E_TOTPOP        0.23679742  0.209960783 -0.0861525983  0.077664639  0.113751822
## M_TOTPOP        0.26617353  0.244079073 -0.0407971062  0.078420374  0.056234593
## E_DAYPOP        0.15901227  0.135308331 -0.0644438350 -0.018283228  0.044114534
## SPL_EJI         0.86769626  0.849689863 -0.4286837329  0.219251524  0.529618513
## RPL_EJI         0.87283460  0.877134806 -0.3955760408  0.259574129  0.518134116
## SPL_SER         1.00000000  0.985952176 -0.4040202170  0.209802604  0.573592414
## RPL_SER         0.98595218  1.000000000 -0.3639024355  0.232964427  0.567275354
## EPL_OZONE      -0.40402022 -0.363902436  1.0000000000 -0.405490496 -0.656016657
## EPL_PM          0.20980260  0.232964427 -0.4054904955  1.000000000  0.117712366
## EPL_DSLPM       0.57359241  0.567275354 -0.6560166574  0.117712366  1.000000000
## EPL_TOTCR       0.60040855  0.590997282 -0.5922467180 -0.035416060  0.912638328
## SPL_EBM_THEME1  0.28495689  0.335868259  0.4175716748 -0.167635113  0.338597535
## RPL_EBM_DOM1    0.26353519  0.314723138  0.4473176797 -0.188555003  0.311645381
## EPL_NPL                 NA           NA            NA           NA           NA
## EPL_TRI         0.30872935  0.302932041 -0.1945416765 -0.434967818  0.424263179
## EPL_TSD         0.06446656  0.047945247 -0.1566698098  0.028302380  0.031767176
## EPL_RMP         0.14040268  0.126937172  0.0421618344  0.364259867 -0.245694425
## EPL_COAL                NA           NA            NA           NA           NA
## EPL_LEAD                NA           NA            NA           NA           NA
## SPL_EBM_THEME2  0.42336364  0.404230974 -0.1728568011 -0.108099780  0.205595069
## RPL_EBM_DOM2    0.43730512  0.423911795 -0.1645777156 -0.109939934  0.228945656
## EPL_PARK       -0.26498814 -0.316114708  0.1027411601 -0.242717122 -0.437531054
## EPL_HOUAGE     -0.10846438 -0.101012806  0.2435356155  0.183241609 -0.164146419
## EPL_WLKIND      0.11890115  0.088419726 -0.0007498688 -0.028208586 -0.027718290
## SPL_EBM_THEME3 -0.03386746 -0.047901513  0.1899072157  0.108187358 -0.165992086
## RPL_EBM_DOM3   -0.02887955 -0.041665110  0.1797728852  0.098511393 -0.155844979
## EPL_RAIL        0.46252365  0.514414254 -0.2600131092  0.550929936  0.313668176
## EPL_ROAD        0.10583298  0.156854453 -0.0481040620  0.209951255  0.312381095
## EPL_AIRPRT      0.12007755  0.083527627  0.0189894942 -0.115957133 -0.001200832
## SPL_EBM_THEME4  0.47947424  0.521156140 -0.2227990218  0.469657077  0.362562241
## RPL_EBM_DOM4    0.48044257  0.527616878 -0.2335744115  0.508653310  0.353549505
## EPL_IMPWTR      0.58742262  0.591646197 -0.3116426487  0.067437483  0.670209666
## SPL_EBM_THEME5  0.58742262  0.591646197 -0.3116426487  0.067437483  0.670209666
## RPL_EBM_DOM5    0.58743188  0.591668966 -0.3117085133  0.067749081  0.670262476
## SPL_EBM         0.53324381  0.530840615 -0.1117936931  0.114761735  0.287073460
## RPL_EBM         0.57178450  0.589087671 -0.1360516566  0.175762632  0.365453091
## EPL_MINRTY      0.64777076  0.640529321 -0.2695310585  0.106143293  0.465308707
## SPL_SVM_DOM1    0.64777076  0.640529321 -0.2695310585  0.106143293  0.465308707
## RPL_SVM_DOM1    0.64777076  0.640529321 -0.2695310585  0.106143293  0.465308707
## EPL_POV200      0.86132762  0.833226524 -0.4657756149  0.145791038  0.585437843
## EPL_NOHSDP      0.79878661  0.785237825 -0.3307873110  0.079814128  0.540909562
## EPL_UNEMP       0.51524859  0.485275325 -0.2289710564  0.167913548  0.263959955
## EPL_RENTER      0.74619829  0.734290758 -0.4263690199  0.214532047  0.490569807
## EPL_HOUBDN      0.77524197  0.781127602 -0.2793740466  0.124128729  0.462721889
## EPL_UNINSUR     0.52020831  0.502657509 -0.2422174915  0.209788495  0.269620738
## EPL_NOINT       0.58965962  0.566484137 -0.3198283037  0.070246274  0.350367247
## SPL_SVM_DOM2    0.88839827  0.864177270 -0.4292829829  0.192081926  0.545331616
## RPL_SVM_DOM2    0.89065401  0.877672184 -0.3900392086  0.185973691  0.525740692
## EPL_AGE65      -0.52733260 -0.502111558  0.3910178194 -0.176559738 -0.461396971
## EPL_AGE17       0.60420158  0.562867599 -0.3803798535  0.089100861  0.433066178
## EPL_DISABL      0.18741996  0.153349626 -0.1207722880 -0.195053460  0.076654092
## EPL_LIMENG      0.64050369  0.614024166 -0.4355719120  0.072104341  0.578633620
## SPL_SVM_DOM3    0.39785785  0.356396027 -0.2202808707 -0.149312707  0.232062481
## RPL_SVM_DOM3    0.41213055  0.371642353 -0.2534842737 -0.114588010  0.255310690
## EPL_MOBILE      0.05780208  0.045622423  0.0498248129  0.073574363 -0.058452436
## EPL_GROUPQ      0.25864346  0.224903295 -0.1688388866  0.142184770  0.072120590
## SPL_SVM_DOM4    0.25120143  0.216176548 -0.1214127767  0.158415073  0.033791401
## RPL_SVM_DOM4    0.23590517  0.201705773 -0.1255589823  0.156038914  0.035190195
## SPL_SVM         0.91128509  0.871340366 -0.4440253424  0.160246404  0.528544921
## RPL_SVM         0.93167729  0.907370313 -0.4184665269  0.170758919  0.517805509
## F_BPHIGH        0.09062852  0.096252164 -0.0500606811  0.074811862  0.001284592
## F_ASTHMA        0.60828882  0.610828608 -0.2056385902  0.127574216  0.369474396
## F_CANCER       -0.45890434 -0.451102288  0.1090961159  0.001306146 -0.322253436
## F_MHLTH         0.62618203  0.577127342 -0.5005157027  0.138448710  0.514378330
## F_DIABETES      0.60008497  0.594064883 -0.2780810656  0.157846128  0.394902804
## F_HVM           0.57186182  0.554228421 -0.3599591907  0.181379720  0.380683779
## RPL_HVM         0.57186182  0.554228421 -0.3599591907  0.181379720  0.380683779
## E_OZONE        -0.46777224 -0.428659693  0.9499947598 -0.491456131 -0.633638854
## E_PM            0.22114459  0.245489244 -0.4115549334  0.999321251  0.130332644
## E_DSLPM         0.50821771  0.485092499 -0.7448073296  0.152086098  0.925446841
## E_TOTCR         0.58156249  0.557591646 -0.6864647278 -0.034041383  0.881819997
## E_NPL                   NA           NA            NA           NA           NA
## E_TRI           0.34071413  0.329454901 -0.2024853225 -0.427425385  0.427061268
## E_TSD           0.06446656  0.047945247 -0.1566698098  0.028302380  0.031767176
## E_RMP           0.13414527  0.124502377  0.0562840890  0.359569488 -0.233639863
## E_COAL                  NA           NA            NA           NA           NA
## E_LEAD                  NA           NA            NA           NA           NA
## E_PARK          0.26289863  0.314583104 -0.1016786951  0.237439544  0.446641296
## E_HOUAGE       -0.09856411 -0.092205212  0.2413673119  0.182853726 -0.164459625
## E_WLKIND       -0.12255745 -0.091167952  0.0063469283  0.026526036  0.025790004
## E_RAIL          0.45465588  0.502503469 -0.2703819252  0.565792846  0.307862072
## E_ROAD          0.07148056  0.119991233 -0.0431789518  0.204695478  0.265776912
## E_AIRPRT        0.08613470  0.058433021 -0.0101561321 -0.057491405  0.011710200
## E_IMPWTR        0.55638218  0.574087857 -0.2024118002  0.058183029  0.627646735
## EP_MINRTY       0.65563020  0.649215821 -0.2701006263  0.126112071  0.464074247
## EP_POV200       0.80204664  0.762280007 -0.4762353054  0.116415163  0.572094493
## EP_NOHSDP       0.74086755  0.700024492 -0.4473700903  0.102731879  0.557169195
## EP_UNEMP        0.46944657  0.438038552 -0.2157114810  0.127250113  0.265522974
## EP_RENTER       0.77218392  0.745425512 -0.5266106291  0.268508283  0.577875001
## EP_HOUBDN       0.70127045  0.687581320 -0.3333092722  0.197937527  0.471330780
## EP_UNINSUR      0.49043286  0.466539989 -0.2585903276  0.182253308  0.277092541
## EP_NOINT        0.54234049  0.512276256 -0.3179910478  0.048810163  0.338068309
## EP_AGE65       -0.49696890 -0.478725003  0.2949709156 -0.111483773 -0.414123355
## EP_AGE17        0.53041881  0.492998865 -0.3388139400  0.069167252  0.391802997
## EP_DISABL       0.15020626  0.122140094 -0.0588487253 -0.183304900  0.044501365
## EP_LIMENG       0.62333777  0.584887716 -0.5030351477  0.258820646  0.591527463
## EP_MOBILE       0.01582468  0.007645493  0.0661825118  0.069930326 -0.104555143
## EP_GROUPQ      -0.05109770 -0.056070078 -0.0009120689  0.013192679 -0.057684273
## EP_BPHIGH       0.16384573  0.168318182 -0.0741811218  0.058537233  0.056369495
## EP_ASTHMA       0.53972592  0.525440594 -0.2713203715  0.158729763  0.329583370
## EP_CANCER      -0.62688169 -0.606695626  0.2992522651 -0.128339430 -0.481525866
## EP_MHLTH        0.73609471  0.697477700 -0.4388848281  0.109123886  0.539932183
## EP_DIABETES     0.60986096  0.581791705 -0.3546924579  0.036819009  0.442053955
## EPL_BPHIGH      0.19872627  0.201418578 -0.0978684059  0.061954722  0.080803486
## EPL_ASTHMA      0.66040154  0.656776170 -0.2741081652  0.161978489  0.408227530
## EPL_CANCER     -0.64963846 -0.628415850  0.3460226356 -0.158106525 -0.495368750
## EPL_DIABETES    0.70902113  0.690546881 -0.3594241782  0.108871825  0.482848881
## EPL_MHLTH       0.79107013  0.751169965 -0.4738583939  0.150326074  0.567114614
##                  EPL_TOTCR SPL_EBM_THEME1 RPL_EBM_DOM1 EPL_NPL      EPL_TRI
## E_TOTPOP        0.09443506    0.038009262  0.033511201      NA -0.026527798
## M_TOTPOP        0.05272375    0.041901746  0.039679649      NA -0.063817597
## E_DAYPOP        0.09829353    0.015444647  0.013425224      NA  0.048827533
## SPL_EJI         0.54179539    0.186606723  0.164712720      NA  0.279978463
## RPL_EJI         0.52664504    0.227586894  0.207292926      NA  0.263246293
## SPL_SER         0.60040855    0.284956886  0.263535185      NA  0.308729347
## RPL_SER         0.59099728    0.335868259  0.314723138      NA  0.302932041
## EPL_OZONE      -0.59224672    0.417571675  0.447317680      NA -0.194541676
## EPL_PM         -0.03541606   -0.167635113 -0.188555003      NA -0.434967818
## EPL_DSLPM       0.91263833    0.338597535  0.311645381      NA  0.424263179
## EPL_TOTCR       1.00000000    0.426643326  0.397113016      NA  0.509230030
## SPL_EBM_THEME1  0.42664333    1.000000000  0.995492236      NA  0.192986337
## RPL_EBM_DOM1    0.39711302    0.995492236  1.000000000      NA  0.191836916
## EPL_NPL                 NA             NA           NA       1           NA
## EPL_TRI         0.50923003    0.192986337  0.191836916      NA  1.000000000
## EPL_TSD         0.07838808   -0.112310096 -0.113439155      NA  0.042951266
## EPL_RMP        -0.20125707   -0.072627426 -0.086608483      NA -0.425070630
## EPL_COAL                NA             NA           NA      NA           NA
## EPL_LEAD                NA             NA           NA      NA           NA
## SPL_EBM_THEME2  0.33091523    0.109118175  0.096115786      NA  0.609635189
## RPL_EBM_DOM2    0.34498985    0.139590807  0.126683721      NA  0.637062127
## EPL_PARK       -0.45105127   -0.513796660 -0.478057324      NA -0.117386231
## EPL_HOUAGE     -0.25870074    0.094180174  0.103853363      NA -0.251818698
## EPL_WLKIND     -0.02218901   -0.040747393 -0.031910857      NA -0.062401127
## SPL_EBM_THEME3 -0.23526175    0.017402271  0.031699815      NA -0.231275978
## RPL_EBM_DOM3   -0.22394932    0.014177918  0.027966417      NA -0.221720051
## EPL_RAIL        0.27856072    0.217801283  0.194245830      NA  0.143588319
## EPL_ROAD        0.25918223    0.352948547  0.325819053      NA  0.001299763
## EPL_AIRPRT      0.07537599    0.054900916  0.060941169      NA  0.073180087
## SPL_EBM_THEME4  0.35405933    0.323864665  0.298399670      NA  0.156414658
## RPL_EBM_DOM4    0.33644497    0.304457000  0.278615945      NA  0.150557671
## EPL_IMPWTR      0.65631427    0.435784578  0.414863221      NA  0.261574097
## SPL_EBM_THEME5  0.65631427    0.435784578  0.414863221      NA  0.261574097
## RPL_EBM_DOM5    0.65629251    0.435806651  0.414885111      NA  0.261440115
## SPL_EBM         0.35153955    0.315671680  0.301810480      NA  0.438397104
## RPL_EBM         0.41199732    0.386721353  0.368554789      NA  0.462606186
## EPL_MINRTY      0.46309872    0.261310406  0.246182348      NA  0.194064392
## SPL_SVM_DOM1    0.46309872    0.261310406  0.246182348      NA  0.194064392
## RPL_SVM_DOM1    0.46309872    0.261310406  0.246182348      NA  0.194064392
## EPL_POV200      0.60825273    0.190194985  0.169849201      NA  0.186357391
## EPL_NOHSDP      0.55096306    0.276663542  0.261787681      NA  0.191592255
## EPL_UNEMP       0.24076370    0.066084342  0.056415727      NA  0.001741317
## EPL_RENTER      0.48801137    0.124829201  0.103604662      NA  0.095680044
## EPL_HOUBDN      0.46845147    0.259412598  0.247894011      NA  0.118651030
## EPL_UNINSUR     0.26206046    0.086324772  0.072703112      NA  0.036651086
## EPL_NOINT       0.36255163    0.051610189  0.044517064      NA  0.178431465
## SPL_SVM_DOM2    0.54845281    0.186563498  0.168212079      NA  0.147563820
## RPL_SVM_DOM2    0.53318474    0.216049803  0.197808015      NA  0.139346834
## EPL_AGE65      -0.44211740   -0.104919158 -0.087561646      NA -0.078087999
## EPL_AGE17       0.44524306    0.081650012  0.065691551      NA  0.135760436
## EPL_DISABL      0.12788727   -0.087137546 -0.087501348      NA  0.136819732
## EPL_LIMENG      0.54659986    0.141141176  0.138467818      NA  0.175387407
## SPL_SVM_DOM3    0.27388249   -0.017038984 -0.017553714      NA  0.184164212
## RPL_SVM_DOM3    0.29452282   -0.021647142 -0.023385609      NA  0.175284013
## EPL_MOBILE     -0.05537384    0.023359316  0.015466929      NA -0.100201911
## EPL_GROUPQ      0.05093613   -0.101501276 -0.106331021      NA  0.034664308
## SPL_SVM_DOM4    0.01701494   -0.076195834 -0.084198928      NA -0.018814990
## RPL_SVM_DOM4    0.01925667   -0.080011273 -0.087103872      NA -0.014619463
## SPL_SVM         0.53722430    0.139600686  0.121895853      NA  0.173587503
## RPL_SVM         0.52896873    0.166391471  0.149053923      NA  0.160955864
## F_BPHIGH        0.02968036   -0.009427114 -0.019198914      NA  0.086844456
## F_ASTHMA        0.38710368    0.253501244  0.242059317      NA  0.083352157
## F_CANCER       -0.33769348   -0.272505896 -0.262212459      NA -0.032384606
## F_MHLTH         0.48442590    0.001398471 -0.018807220      NA  0.204914006
## F_DIABETES      0.38388035    0.172655015  0.160046204      NA  0.169680606
## F_HVM           0.37771492    0.062867095  0.045160206      NA  0.196511039
## RPL_HVM         0.37771492    0.062867095  0.045160206      NA  0.196511039
## E_OZONE        -0.56929819    0.347831493  0.377536175      NA -0.100098825
## E_PM           -0.02242667   -0.159801207 -0.181080242      NA -0.414482911
## E_DSLPM         0.80365188    0.107050248  0.088296157      NA  0.394468255
## E_TOTCR         0.96790166    0.262457904  0.236445119      NA  0.528749343
## E_NPL                   NA             NA           NA      NA           NA
## E_TRI           0.52416982    0.200533258  0.196014054      NA  0.963097211
## E_TSD           0.07838808   -0.112310096 -0.113439155      NA  0.042951266
## E_RMP          -0.19548357   -0.046674352 -0.057373130      NA -0.431159469
## E_COAL                  NA             NA           NA      NA           NA
## E_LEAD                  NA             NA           NA      NA           NA
## E_PARK          0.45809461    0.522622861  0.486470510      NA  0.115558251
## E_HOUAGE       -0.25822624    0.091533612  0.101469322      NA -0.251081371
## E_WLKIND        0.01829926    0.043231621  0.034377165      NA  0.056343199
## E_RAIL          0.25359260    0.183724485  0.160536284      NA  0.123387513
## E_ROAD          0.20668811    0.293575534  0.269314204      NA -0.011489750
## E_AIRPRT        0.05363417    0.020483127  0.024817888      NA  0.048014694
## E_IMPWTR        0.62470233    0.534639078  0.511168620      NA  0.235565673
## EP_MINRTY       0.46318639    0.267715739  0.251503422      NA  0.184168508
## EP_POV200       0.59751211    0.151260337  0.130632898      NA  0.212476186
## EP_NOHSDP       0.55717208    0.141142220  0.126585365      NA  0.215051049
## EP_UNEMP        0.27054576    0.097893937  0.088992811      NA  0.020096240
## EP_RENTER       0.56071572    0.106881266  0.085732156      NA  0.102321951
## EP_HOUBDN       0.46662100    0.215942477  0.201161486      NA  0.069158787
## EP_UNINSUR      0.26898163    0.063182946  0.050521786      NA  0.058407643
## EP_NOINT        0.35436592    0.034703911  0.029634659      NA  0.203403721
## EP_AGE65       -0.39903419   -0.153100684 -0.137967570      NA -0.076331840
## EP_AGE17        0.38860847    0.062886272  0.052564591      NA  0.128508737
## EP_DISABL       0.12030412   -0.016989939 -0.027866235      NA  0.126213932
## EP_LIMENG       0.49695376    0.076484393  0.063262797      NA  0.054913722
## EP_MOBILE      -0.10546776   -0.017784746 -0.028370284      NA -0.091822548
## EP_GROUPQ      -0.01327566   -0.025295719 -0.031492481      NA -0.026776012
## EP_BPHIGH       0.07175820    0.008750381  0.001018599      NA  0.156466898
## EP_ASTHMA       0.33347592    0.114799784  0.096877803      NA  0.151576180
## EP_CANCER      -0.48134026   -0.252373655 -0.233497560      NA -0.108669031
## EP_MHLTH        0.54507544    0.138218859  0.120503494      NA  0.218033515
## EP_DIABETES     0.47042865    0.123235831  0.105066503      NA  0.279482035
## EPL_BPHIGH      0.09739123    0.010304047  0.003616770      NA  0.185611430
## EPL_ASTHMA      0.41953630    0.217779047  0.197245339      NA  0.149973821
## EPL_CANCER     -0.49076434   -0.214421889 -0.198109371      NA -0.102946278
## EPL_DIABETES    0.49251270    0.176555493  0.159763160      NA  0.263771910
## EPL_MHLTH       0.56784545    0.136835308  0.117036765      NA  0.201800660
##                      EPL_TSD      EPL_RMP EPL_COAL EPL_LEAD SPL_EBM_THEME2
## E_TOTPOP       -0.0274357505  0.053541072       NA       NA    0.015747018
## M_TOTPOP       -0.0302984012  0.070376395       NA       NA   -0.006330987
## E_DAYPOP        0.1657402457  0.187665717       NA       NA    0.227140161
## SPL_EJI        -0.0149740580 -0.047129642       NA       NA    0.227385803
## RPL_EJI        -0.0051302064 -0.027357417       NA       NA    0.229258930
## SPL_SER         0.0644665565  0.140402678       NA       NA    0.423363639
## RPL_SER         0.0479452470  0.126937172       NA       NA    0.404230974
## EPL_OZONE      -0.1566698098  0.042161834       NA       NA   -0.172856801
## EPL_PM          0.0283023798  0.364259867       NA       NA   -0.108099780
## EPL_DSLPM       0.0317671760 -0.245694425       NA       NA    0.205595069
## EPL_TOTCR       0.0783880810 -0.201257071       NA       NA    0.330915230
## SPL_EBM_THEME1 -0.1123100959 -0.072627426       NA       NA    0.109118175
## RPL_EBM_DOM1   -0.1134391549 -0.086608483       NA       NA    0.096115786
## EPL_NPL                   NA           NA       NA       NA             NA
## EPL_TRI         0.0429512662 -0.425070630       NA       NA    0.609635189
## EPL_TSD         1.0000000000  0.120206297       NA       NA    0.278509748
## EPL_RMP         0.1202062973  1.000000000       NA       NA    0.447956692
## EPL_COAL                  NA           NA        1       NA             NA
## EPL_LEAD                  NA           NA       NA        1             NA
## SPL_EBM_THEME2  0.2785097475  0.447956692       NA       NA    1.000000000
## RPL_EBM_DOM2    0.1394121791  0.414746193       NA       NA    0.979501699
## EPL_PARK       -0.0042357890 -0.032197462       NA       NA   -0.140412866
## EPL_HOUAGE     -0.1222079044  0.150314601       NA       NA   -0.132346396
## EPL_WLKIND      0.0787410995  0.020177361       NA       NA   -0.032278845
## SPL_EBM_THEME3 -0.0499299621  0.122500719       NA       NA   -0.126122727
## RPL_EBM_DOM3   -0.0606446221  0.116715054       NA       NA   -0.123261008
## EPL_RAIL        0.0121470949  0.084695329       NA       NA    0.210765347
## EPL_ROAD       -0.0051296945 -0.069363482       NA       NA   -0.057715646
## EPL_AIRPRT     -0.0052781575  0.212842522       NA       NA    0.248383602
## SPL_EBM_THEME4  0.0058172590  0.153786302       NA       NA    0.280263497
## RPL_EBM_DOM4    0.0060755477  0.131134117       NA       NA    0.255643154
## EPL_IMPWTR      0.0300239152 -0.059233560       NA       NA    0.205666505
## SPL_EBM_THEME5  0.0300239152 -0.059233560       NA       NA    0.205666505
## RPL_EBM_DOM5    0.0299704952 -0.059203726       NA       NA    0.205555551
## SPL_EBM         0.1793230472  0.424801387       NA       NA    0.802500753
## RPL_EBM         0.0955839242  0.343380872       NA       NA    0.745957573
## EPL_MINRTY     -0.0035761585 -0.101723260       NA       NA    0.100530258
## SPL_SVM_DOM1   -0.0035761585 -0.101723260       NA       NA    0.100530258
## RPL_SVM_DOM1   -0.0035761585 -0.101723260       NA       NA    0.100530258
## EPL_POV200      0.0231118450  0.039910276       NA       NA    0.215734271
## EPL_NOHSDP     -0.0137064998 -0.031488784       NA       NA    0.155771639
## EPL_UNEMP       0.0308180322  0.048348153       NA       NA    0.046485180
## EPL_RENTER      0.0292949026  0.106275767       NA       NA    0.185197327
## EPL_HOUBDN      0.0143047804  0.050127733       NA       NA    0.158061682
## EPL_UNINSUR     0.0776121643  0.071180277       NA       NA    0.105583507
## EPL_NOINT      -0.0375231166 -0.127109679       NA       NA    0.059558973
## SPL_SVM_DOM2    0.0258450985  0.029767492       NA       NA    0.170312234
## RPL_SVM_DOM2    0.0285580977  0.042114349       NA       NA    0.173158085
## EPL_AGE65      -0.0685996975 -0.046898770       NA       NA   -0.123773238
## EPL_AGE17       0.0481932640 -0.040367791       NA       NA    0.103102526
## EPL_DISABL      0.0180854079 -0.189821990       NA       NA   -0.025524276
## EPL_LIMENG     -0.0327240263  0.041655651       NA       NA    0.199051389
## SPL_SVM_DOM3   -0.0142739571 -0.159840115       NA       NA    0.040741676
## RPL_SVM_DOM3   -0.0004315695 -0.142814509       NA       NA    0.048397012
## EPL_MOBILE     -0.0216838799  0.095797679       NA       NA   -0.018762775
## EPL_GROUPQ      0.0672258159  0.038610325       NA       NA    0.074900368
## SPL_SVM_DOM4    0.0474452102  0.079878680       NA       NA    0.055485257
## RPL_SVM_DOM4    0.0579687572  0.077877025       NA       NA    0.059269112
## SPL_SVM         0.0288240197 -0.006581657       NA       NA    0.165189450
## RPL_SVM         0.0340586354  0.014305053       NA       NA    0.171310626
## F_BPHIGH       -0.0464497820 -0.218926516       NA       NA   -0.106784538
## F_ASTHMA        0.0232974312 -0.055936757       NA       NA    0.036275963
## F_CANCER       -0.0180662871 -0.023075228       NA       NA   -0.052961601
## F_MHLTH        -0.0603938442 -0.091089185       NA       NA    0.112145323
## F_DIABETES     -0.1134977905 -0.137623004       NA       NA    0.031966733
## F_HVM          -0.0801584128 -0.198536139       NA       NA    0.011122415
## RPL_HVM        -0.0801584128 -0.198536139       NA       NA    0.011122415
## E_OZONE        -0.1045026123 -0.065063562       NA       NA   -0.165073029
## E_PM            0.0296409991  0.349192690       NA       NA   -0.100891064
## E_DSLPM         0.0234050628 -0.284350478       NA       NA    0.143356168
## E_TOTCR         0.1190529215 -0.230738860       NA       NA    0.330446706
## E_NPL                     NA           NA       NA       NA             NA
## E_TRI           0.0475294973 -0.386900033       NA       NA    0.606864672
## E_TSD           1.0000000000  0.120206297       NA       NA    0.278509748
## E_RMP           0.0341492711  0.896123297       NA       NA    0.343122863
## E_COAL                    NA           NA       NA       NA             NA
## E_LEAD                    NA           NA       NA       NA             NA
## E_PARK          0.0041698278  0.031696072       NA       NA    0.138226307
## E_HOUAGE       -0.1235347631  0.148042179       NA       NA   -0.133727587
## E_WLKIND       -0.0815413585 -0.016706045       NA       NA    0.028992462
## E_RAIL          0.0127833370  0.089576305       NA       NA    0.195542280
## E_ROAD          0.0056336013 -0.089957477       NA       NA   -0.085836689
## E_AIRPRT       -0.0035611889  0.161622584       NA       NA    0.181412698
## E_IMPWTR        0.0223267351 -0.046561360       NA       NA    0.190272309
## EP_MINRTY       0.0017535280 -0.078913526       NA       NA    0.110908365
## EP_POV200       0.0096792609  0.000980073       NA       NA    0.206298440
## EP_NOHSDP      -0.0379191476 -0.069960507       NA       NA    0.142696126
## EP_UNEMP        0.0082596533  0.025005213       NA       NA    0.041439288
## EP_RENTER       0.0285424398  0.116686274       NA       NA    0.200221472
## EP_HOUBDN      -0.0078545072  0.074778915       NA       NA    0.128194901
## EP_UNINSUR      0.0930861881  0.041250770       NA       NA    0.103455870
## EP_NOINT       -0.0400449515 -0.148683350       NA       NA    0.065087803
## EP_AGE65       -0.0877480636 -0.053899001       NA       NA   -0.130575343
## EP_AGE17        0.0375029460 -0.073120735       NA       NA    0.067165490
## EP_DISABL       0.0025869926 -0.135419607       NA       NA    0.007871444
## EP_LIMENG      -0.0543647464  0.158825284       NA       NA    0.178769006
## EP_MOBILE      -0.0177569198  0.067653614       NA       NA   -0.033817499
## EP_GROUPQ       0.0812986482  0.062434340       NA       NA    0.037795771
## EP_BPHIGH      -0.0727846350 -0.326134775       NA       NA   -0.133532099
## EP_ASTHMA      -0.0400409764 -0.195431172       NA       NA   -0.023978069
## EP_CANCER      -0.0624671550 -0.108306518       NA       NA   -0.203903812
## EP_MHLTH       -0.0006942556 -0.069070451       NA       NA    0.151381971
## EP_DIABETES    -0.0446842377 -0.208489024       NA       NA    0.087318000
## EPL_BPHIGH     -0.0860034297 -0.348862864       NA       NA   -0.126421723
## EPL_ASTHMA     -0.0180318128 -0.116022446       NA       NA    0.044184971
## EPL_CANCER     -0.0503484066 -0.089834324       NA       NA   -0.181237072
## EPL_DIABETES   -0.0344711114 -0.180298396       NA       NA    0.097294950
## EPL_MHLTH       0.0085251856 -0.045985577       NA       NA    0.156432407
##                RPL_EBM_DOM2     EPL_PARK   EPL_HOUAGE    EPL_WLKIND
## E_TOTPOP        0.031836776  0.019553936  0.028027260  0.2685063650
## M_TOTPOP        0.003350790  0.033953987 -0.003912778  0.2719731649
## E_DAYPOP        0.192928315  0.038519067 -0.052436618  0.0597487229
## SPL_EJI         0.245751889 -0.221954214 -0.170076081  0.1552373213
## RPL_EJI         0.248333400 -0.266994837 -0.146944433  0.1326652347
## SPL_SER         0.437305123 -0.264988136 -0.108464376  0.1189011480
## RPL_SER         0.423911795 -0.316114708 -0.101012806  0.0884197260
## EPL_OZONE      -0.164577716  0.102741160  0.243535615 -0.0007498688
## EPL_PM         -0.109939934 -0.242717122  0.183241609 -0.0282085864
## EPL_DSLPM       0.228945656 -0.437531054 -0.164146419 -0.0277182897
## EPL_TOTCR       0.344989847 -0.451051270 -0.258700740 -0.0221890094
## SPL_EBM_THEME1  0.139590807 -0.513796660  0.094180174 -0.0407473932
## RPL_EBM_DOM1    0.126683721 -0.478057324  0.103853363 -0.0319108572
## EPL_NPL                  NA           NA           NA            NA
## EPL_TRI         0.637062127 -0.117386231 -0.251818698 -0.0624011265
## EPL_TSD         0.139412179 -0.004235789 -0.122207904  0.0787410995
## EPL_RMP         0.414746193 -0.032197462  0.150314601  0.0201773611
## EPL_COAL                 NA           NA           NA            NA
## EPL_LEAD                 NA           NA           NA            NA
## SPL_EBM_THEME2  0.979501699 -0.140412866 -0.132346396 -0.0322788454
## RPL_EBM_DOM2    1.000000000 -0.152809576 -0.122281181 -0.0532398459
## EPL_PARK       -0.152809576  1.000000000 -0.009673341  0.0904999772
## EPL_HOUAGE     -0.122281181 -0.009673341  1.000000000  0.1550684735
## EPL_WLKIND     -0.053239846  0.090499977  0.155068474  1.0000000000
## SPL_EBM_THEME3 -0.130637574  0.103362145  0.838856411  0.6644191459
## RPL_EBM_DOM3   -0.124438620  0.112135293  0.791126899  0.6942228593
## EPL_RAIL        0.220041267 -0.410074280  0.032927192 -0.0550527728
## EPL_ROAD       -0.020360401 -0.614757384  0.147035024 -0.0719297862
## EPL_AIRPRT      0.184586540 -0.007355506 -0.010749280  0.0881845204
## SPL_EBM_THEME4  0.268440747 -0.545768645  0.070050210 -0.0254513877
## RPL_EBM_DOM4    0.252253575 -0.525614017  0.071303191 -0.0301711449
## EPL_IMPWTR      0.208617102 -0.380246308 -0.105457318  0.0083896174
## SPL_EBM_THEME5  0.208617102 -0.380246308 -0.105457318  0.0083896174
## RPL_EBM_DOM5    0.208500161 -0.380289441 -0.105282314  0.0083574287
## SPL_EBM         0.784181164 -0.312747835  0.298991840  0.2637381118
## RPL_EBM         0.760511832 -0.413419241  0.284761977  0.2121887246
## EPL_MINRTY      0.119063218 -0.164898023 -0.208600232  0.1182704468
## SPL_SVM_DOM1    0.119063218 -0.164898023 -0.208600232  0.1182704468
## RPL_SVM_DOM1    0.119063218 -0.164898023 -0.208600232  0.1182704468
## EPL_POV200      0.232851987 -0.146630472 -0.257196871  0.0616291468
## EPL_NOHSDP      0.178389995 -0.189302928 -0.228682769  0.0415484928
## EPL_UNEMP       0.044955393 -0.061832330 -0.071443587  0.1131606007
## EPL_RENTER      0.201159143 -0.147623706 -0.143439973  0.0497844182
## EPL_HOUBDN      0.170064865 -0.082098188 -0.163768879  0.0286358729
## EPL_UNINSUR     0.101022834 -0.049479157 -0.077628055 -0.0141648404
## EPL_NOINT       0.065754903 -0.079235641 -0.277261166  0.1010488989
## SPL_SVM_DOM2    0.181892090 -0.136837227 -0.226740299  0.0737287881
## RPL_SVM_DOM2    0.185714453 -0.142458330 -0.216414925  0.0683545548
## EPL_AGE65      -0.130091964  0.089834113  0.231338787  0.0131230939
## EPL_AGE17       0.110710674 -0.106389154 -0.294067411  0.0087928701
## EPL_DISABL     -0.030448172  0.044155930 -0.076803611  0.0725867982
## EPL_LIMENG      0.235824333 -0.120525569 -0.167328107 -0.0104385702
## SPL_SVM_DOM3    0.051560915 -0.030296022 -0.154449619  0.0545141428
## RPL_SVM_DOM3    0.058310650 -0.045440110 -0.162333670  0.0422875342
## EPL_MOBILE     -0.022956425 -0.030218104  0.109361782  0.0233952064
## EPL_GROUPQ      0.056349801  0.033298321 -0.219624928 -0.1164666477
## SPL_SVM_DOM4    0.037445146  0.014031060 -0.136274245 -0.0890871500
## RPL_SVM_DOM4    0.038982933  0.013152489 -0.134816490 -0.0903088097
## SPL_SVM         0.173520866 -0.123118527 -0.270571098  0.0564091016
## RPL_SVM         0.181384658 -0.130908838 -0.254613219  0.0469223215
## F_BPHIGH       -0.101641740 -0.064731235 -0.042366227  0.1430608252
## F_ASTHMA        0.043574415 -0.181813563 -0.140598385  0.1245054588
## F_CANCER       -0.061487498  0.128144304  0.177516415 -0.0276231710
## F_MHLTH         0.130527375 -0.084163326 -0.299305057  0.0724528904
## F_DIABETES      0.056974493 -0.158167635 -0.135516895  0.0980545445
## F_HVM           0.029440863 -0.138375542 -0.187385794  0.1539210143
## RPL_HVM         0.029440863 -0.138375542 -0.187385794  0.1539210143
## E_OZONE        -0.160424340  0.150559773  0.214520437  0.0024282690
## E_PM           -0.102784945 -0.252658442  0.178638640 -0.0330481179
## E_DSLPM         0.163830053 -0.172596367 -0.164506906  0.0024881457
## E_TOTCR         0.337265448 -0.290855426 -0.282768918  0.0088411151
## E_NPL                    NA           NA           NA            NA
## E_TRI           0.629408560 -0.103912935 -0.266071222 -0.0748555800
## E_TSD           0.139412179 -0.004235789 -0.122207904  0.0787410995
## E_RMP           0.345204762 -0.027119845  0.168090693  0.0285204344
## E_COAL                   NA           NA           NA            NA
## E_LEAD                   NA           NA           NA            NA
## E_PARK          0.150429971 -0.997432555  0.012842041 -0.0893822296
## E_HOUAGE       -0.124291225 -0.007147892  0.997562969  0.1582561348
## E_WLKIND        0.049502194 -0.090129534 -0.156606681 -0.9953438933
## E_RAIL          0.202355984 -0.376793799  0.051542890 -0.0685464881
## E_ROAD         -0.045055195 -0.528494556  0.146240353 -0.0702138992
## E_AIRPRT        0.133659634 -0.004962782 -0.008759735  0.0189889910
## E_IMPWTR        0.190060640 -0.497401248 -0.078525931  0.0011482188
## EP_MINRTY       0.127452928 -0.178276677 -0.201077156  0.1195953051
## EP_POV200       0.223847971 -0.126106496 -0.270817768  0.0957925294
## EP_NOHSDP       0.169042912 -0.134062809 -0.219888092  0.0953650967
## EP_UNEMP        0.032612698 -0.067780865 -0.073034636  0.1283088875
## EP_RENTER       0.220206609 -0.142212961 -0.167462954  0.0682266030
## EP_HOUBDN       0.134755502 -0.098877679 -0.142754999  0.0458791385
## EP_UNINSUR      0.099685162 -0.050027769 -0.063239004  0.0040662948
## EP_NOINT        0.073324698 -0.073512125 -0.265890125  0.1358317725
## EP_AGE65       -0.132023427  0.063811507  0.221436113  0.0491738921
## EP_AGE17        0.074920807 -0.093161785 -0.284420681  0.0344459547
## EP_DISABL       0.006157561  0.032055882 -0.010672721  0.0977588422
## EP_LIMENG       0.215796902 -0.102288713 -0.034525574  0.0120623395
## EP_MOBILE      -0.037171877 -0.024745592  0.110700188 -0.0014088667
## EP_GROUPQ       0.017959260  0.072471729 -0.047514833 -0.0179291513
## EP_BPHIGH      -0.122366888 -0.088192505 -0.038972928  0.1988599480
## EP_ASTHMA      -0.015813661 -0.120552460 -0.236022453  0.1782583108
## EP_CANCER      -0.206628667  0.108154514  0.220545429  0.0361372792
## EP_MHLTH        0.165150532 -0.111401035 -0.279362115  0.1028982691
## EP_DIABETES     0.113043802 -0.138833019 -0.219821892  0.2063477538
## EPL_BPHIGH     -0.112854794 -0.095711980 -0.064354407  0.1861042626
## EPL_ASTHMA      0.054500693 -0.158135593 -0.211673173  0.1176467572
## EPL_CANCER     -0.185696943  0.127818388  0.235221283  0.0107675480
## EPL_DIABETES    0.125853235 -0.199783205 -0.187348561  0.1600281024
## EPL_MHLTH       0.168493146 -0.124698627 -0.284204020  0.0655590577
##                SPL_EBM_THEME3 RPL_EBM_DOM3      EPL_RAIL      EPL_ROAD
## E_TOTPOP          0.167826777  0.176313053  0.0703799141 -0.0230385786
## M_TOTPOP          0.146463230  0.156045555  0.0667434915 -0.0758371178
## E_DAYPOP         -0.004873365 -0.004302228  0.0447312975 -0.1466970627
## SPL_EJI          -0.058076270 -0.046663672  0.4198945789  0.0829286351
## RPL_EJI          -0.055605142 -0.043951243  0.4932905949  0.1131574844
## SPL_SER          -0.033867464 -0.028879554  0.4625236504  0.1058329848
## RPL_SER          -0.047901513 -0.041665110  0.5144142542  0.1568544533
## EPL_OZONE         0.189907216  0.179772885 -0.2600131092 -0.0481040620
## EPL_PM            0.108187358  0.098511393  0.5509299356  0.2099512552
## EPL_DSLPM        -0.165992086 -0.155844979  0.3136681760  0.3123810946
## EPL_TOTCR        -0.235261754 -0.223949321  0.2785607191  0.2591822297
## SPL_EBM_THEME1    0.017402271  0.014177918  0.2178012834  0.3529485475
## RPL_EBM_DOM1      0.031699815  0.027966417  0.1942458299  0.3258190528
## EPL_NPL                    NA           NA            NA            NA
## EPL_TRI          -0.231275978 -0.221720051  0.1435883188  0.0012997632
## EPL_TSD          -0.049929962 -0.060644622  0.0121470949 -0.0051296945
## EPL_RMP           0.122500719  0.116715054  0.0846953286 -0.0693634821
## EPL_COAL                   NA           NA            NA            NA
## EPL_LEAD                   NA           NA            NA            NA
## SPL_EBM_THEME2   -0.126122727 -0.123261008  0.2107653475 -0.0577156461
## RPL_EBM_DOM2     -0.130637574 -0.124438620  0.2200412666 -0.0203604014
## EPL_PARK          0.103362145  0.112135293 -0.4100742796 -0.6147573842
## EPL_HOUAGE        0.838856411  0.791126899  0.0329271923  0.1470350239
## EPL_WLKIND        0.664419146  0.694222859 -0.0550527728 -0.0719297862
## SPL_EBM_THEME3    1.000000000  0.980627890 -0.0302264761  0.0342164545
## RPL_EBM_DOM3      0.980627890  1.000000000 -0.0274796632  0.0043087562
## EPL_RAIL         -0.030226476 -0.027479663  1.0000000000  0.2402699942
## EPL_ROAD          0.034216454  0.004308756  0.2402699942  1.0000000000
## EPL_AIRPRT        0.039194930  0.038467347 -0.0131136129 -0.5152649739
## SPL_EBM_THEME4    0.005487987 -0.002344521  0.9047147339  0.2700629657
## RPL_EBM_DOM4      0.005120361 -0.003026523  0.9508212368  0.2961119086
## EPL_IMPWTR       -0.098564395 -0.084239776  0.2337696022  0.2628146628
## SPL_EBM_THEME5   -0.098564395 -0.084239776  0.2337696022  0.2628146628
## RPL_EBM_DOM5     -0.098452283 -0.084141029  0.2338474761  0.2629172136
## SPL_EBM           0.349459606  0.341447029  0.4768229895  0.1141012261
## RPL_EBM           0.304579602  0.293658956  0.5769911032  0.2681720615
## EPL_MINRTY       -0.103686841 -0.085137599  0.2251723555  0.0338805017
## SPL_SVM_DOM1     -0.103686841 -0.085137599  0.2251723555  0.0338805017
## RPL_SVM_DOM1     -0.103686841 -0.085137599  0.2251723555  0.0338805017
## EPL_POV200       -0.169955398 -0.154852510  0.2644038087  0.0374092583
## EPL_NOHSDP       -0.161922496 -0.160967796  0.2123582908  0.0989376160
## EPL_UNEMP         0.003514276  0.017694135  0.1461135935 -0.0180541962
## EPL_RENTER       -0.090494822 -0.083373815  0.3259213715  0.0819498243
## EPL_HOUBDN       -0.113268950 -0.100655151  0.2934148780  0.0209793983
## EPL_UNINSUR      -0.069367586 -0.069167342  0.2491910032  0.0007849773
## EPL_NOINT        -0.159604957 -0.154224629  0.2005765504 -0.0153499485
## SPL_SVM_DOM2     -0.139788869 -0.128907408  0.3112558207  0.0325610750
## RPL_SVM_DOM2     -0.135246240 -0.124241274  0.3193250064  0.0343286927
## EPL_AGE65         0.187412295  0.172071526 -0.1561310891 -0.0773677713
## EPL_AGE17        -0.223949671 -0.213982220  0.1285449080  0.0143361951
## EPL_DISABL       -0.015979697 -0.007078403 -0.1871168952 -0.1021251694
## EPL_LIMENG       -0.139493059 -0.135824397  0.1568891225  0.0451873965
## SPL_SVM_DOM3     -0.089017173 -0.086265553 -0.0713826647 -0.0889751383
## RPL_SVM_DOM3     -0.102529857 -0.103248008 -0.0474611199 -0.0677111582
## EPL_MOBILE        0.093427886  0.096149178  0.0602221139  0.0068225007
## EPL_GROUPQ       -0.226952811 -0.219195284  0.1111745432 -0.0232508456
## SPL_SVM_DOM4     -0.150341746 -0.142327270  0.1251748883 -0.0167386899
## RPL_SVM_DOM4     -0.149956406 -0.142522814  0.1230468641 -0.0055910045
## SPL_SVM          -0.181437230 -0.168538236  0.2732236815 -0.0005663096
## RPL_SVM          -0.175000969 -0.164255111  0.2925310815  0.0066479703
## F_BPHIGH          0.041498900  0.045201643  0.0951663254  0.0418985036
## F_ASTHMA         -0.049979951 -0.037525660  0.2861420072  0.0749334947
## F_CANCER          0.127041735  0.122624268 -0.0506351820 -0.0962142336
## F_MHLTH          -0.192052122 -0.180534782  0.1810234682  0.0258228713
## F_DIABETES       -0.059011709 -0.042627358  0.3142787153  0.0563966425
## F_HVM            -0.066713634 -0.052169591  0.2951364650  0.0458305588
## RPL_HVM          -0.066713634 -0.052169591  0.2951364650  0.0458305588
## E_OZONE           0.172657040  0.156582170 -0.3317833860 -0.0726290956
## E_PM              0.101475640  0.092234813  0.5678931502  0.2144641700
## E_DSLPM          -0.133569453 -0.125954956  0.2106224046  0.0972826432
## E_TOTCR          -0.226759788 -0.214063718  0.2235819885  0.1262038810
## E_NPL                      NA           NA            NA            NA
## E_TRI            -0.247959001 -0.238715020  0.1688726508 -0.0044563693
## E_TSD            -0.049929962 -0.060644622  0.0121470949 -0.0051296945
## E_RMP             0.140762129  0.140731038  0.0735972377 -0.0382578163
## E_COAL                     NA           NA            NA            NA
## E_LEAD                     NA           NA            NA            NA
## E_PARK           -0.100204590 -0.108892696  0.4036884572  0.6442295946
## E_HOUAGE          0.838897768  0.781416145  0.0324017855  0.1482528403
## E_WLKIND         -0.663036172 -0.692118442  0.0525332681  0.0733929824
## E_RAIL           -0.021421010 -0.020773412  0.9825606595  0.2321240507
## E_ROAD            0.039863419  0.009945518  0.2088802288  0.9866322350
## E_AIRPRT          0.003362697 -0.001980974 -0.0073494118 -0.2534010247
## E_IMPWTR         -0.089363822 -0.076811157  0.2480418549  0.3863714739
## EP_MINRTY        -0.098110592 -0.079356606  0.2455539611  0.0432141662
## EP_POV200        -0.160474043 -0.143165814  0.2400838113  0.0152552614
## EP_NOHSDP        -0.122721074 -0.121693450  0.2156711138  0.0753201406
## EP_UNEMP          0.010151329  0.022783567  0.1495390316  0.0016237766
## EP_RENTER        -0.098319500 -0.088902970  0.3187566732  0.0737812258
## EP_HOUBDN        -0.089087788 -0.078325270  0.2917053280  0.0374750812
## EP_UNINSUR       -0.048655470 -0.049572536  0.2247331535  0.0199489283
## EP_NOINT         -0.131820188 -0.130056288  0.1612874242 -0.0039320194
## EP_AGE65          0.197855550  0.187357397 -0.1072427031 -0.0449074793
## EP_AGE17         -0.201950494 -0.192702233  0.1142019152  0.0125814695
## EP_DISABL         0.046868693  0.058722874 -0.1623750581 -0.0766596544
## EP_LIMENG        -0.025854129 -0.023001059  0.2148696185  0.0694345544
## EP_MOBILE         0.081340156  0.077296115  0.0410933559 -0.0085633010
## EP_GROUPQ        -0.041139690 -0.038594862 -0.0005683839  0.0151211265
## EP_BPHIGH         0.072842072  0.084283381  0.1470168019 -0.0058469689
## EP_ASTHMA        -0.089174274 -0.081311006  0.2375822851  0.0440671099
## EP_CANCER         0.192854436  0.178849666 -0.1874508878 -0.0467420233
## EP_MHLTH         -0.162173224 -0.155728327  0.2215591860  0.0417640101
## EP_DIABETES      -0.062846585 -0.053610275  0.2102887166  0.0196435957
## EPL_BPHIGH        0.046294334  0.053700478  0.1650957876  0.0055121905
## EPL_ASTHMA       -0.105929271 -0.094094858  0.2737632750  0.0732419209
## EPL_CANCER        0.191410960  0.176815432 -0.2088564595 -0.0653142222
## EPL_DIABETES     -0.067162918 -0.053698937  0.2647991438  0.0481931985
## EPL_MHLTH        -0.186877204 -0.178147537  0.2459709984  0.0530883124
##                   EPL_AIRPRT SPL_EBM_THEME4 RPL_EBM_DOM4   EPL_IMPWTR
## E_TOTPOP       -0.0097371705    0.046254624  0.051988494  0.038561491
## M_TOTPOP        0.0276524093    0.044598774  0.045464679  0.052456103
## E_DAYPOP        0.3312159259    0.154156026  0.099983777 -0.021906638
## SPL_EJI         0.0767821058    0.414960061  0.419059170  0.513525204
## RPL_EJI         0.0628077969    0.478998831  0.488494966  0.521641736
## SPL_SER         0.1200775475    0.479474242  0.480442573  0.587422618
## RPL_SER         0.0835276266    0.521156140  0.527616878  0.591646197
## EPL_OZONE       0.0189894942   -0.222799022 -0.233574412 -0.311642649
## EPL_PM         -0.1159571326    0.469657077  0.508653310  0.067437483
## EPL_DSLPM      -0.0012008324    0.362562241  0.353549505  0.670209666
## EPL_TOTCR       0.0753759915    0.354059331  0.336444966  0.656314273
## SPL_EBM_THEME1  0.0549009161    0.323864665  0.304457000  0.435784578
## RPL_EBM_DOM1    0.0609411689    0.298399670  0.278615945  0.414863221
## EPL_NPL                   NA             NA           NA           NA
## EPL_TRI         0.0731800870    0.156414658  0.150557671  0.261574097
## EPL_TSD        -0.0052781575    0.005817259  0.006075548  0.030023915
## EPL_RMP         0.2128425221    0.153786302  0.131134117 -0.059233560
## EPL_COAL                  NA             NA           NA           NA
## EPL_LEAD                  NA             NA           NA           NA
## SPL_EBM_THEME2  0.2483836019    0.280263497  0.255643154  0.205666505
## RPL_EBM_DOM2    0.1845865402    0.268440747  0.252253575  0.208617102
## EPL_PARK       -0.0073555061   -0.545768645 -0.525614017 -0.380246308
## EPL_HOUAGE     -0.0107492802    0.070050210  0.071303191 -0.105457318
## EPL_WLKIND      0.0881845204   -0.025451388 -0.030171145  0.008389617
## SPL_EBM_THEME3  0.0391949295    0.005487987  0.005120361 -0.098564395
## RPL_EBM_DOM3    0.0384673471   -0.002344521 -0.003026523 -0.084239776
## EPL_RAIL       -0.0131136129    0.904714734  0.950821237  0.233769602
## EPL_ROAD       -0.5152649739    0.270062966  0.296111909  0.262814663
## EPL_AIRPRT      1.0000000000    0.318416394  0.199782836  0.038677566
## SPL_EBM_THEME4  0.3184163941    1.000000000  0.987883516  0.299684616
## RPL_EBM_DOM4    0.1997828359    0.987883516  1.000000000  0.286260470
## EPL_IMPWTR      0.0386775655    0.299684616  0.286260470  1.000000000
## SPL_EBM_THEME5  0.0386775655    0.299684616  0.286260470  1.000000000
## RPL_EBM_DOM5    0.0386433267    0.299765900  0.286346658  0.999999557
## SPL_EBM         0.3130613707    0.590082394  0.564927976  0.336408874
## RPL_EBM         0.1640215634    0.649635697  0.645301114  0.379404641
## EPL_MINRTY      0.0537513447    0.225326787  0.226996274  0.594612164
## SPL_SVM_DOM1    0.0537513447    0.225326787  0.226996274  0.594612164
## RPL_SVM_DOM1    0.0537513447    0.225326787  0.226996274  0.594612164
## EPL_POV200      0.0557187283    0.260130488  0.259541100  0.594953539
## EPL_NOHSDP      0.0356642958    0.226883858  0.223831984  0.594456046
## EPL_UNEMP       0.0645032189    0.147886665  0.148959421  0.265252223
## EPL_RENTER      0.0048785196    0.300606743  0.308501022  0.429836124
## EPL_HOUBDN      0.0365915229    0.269416481  0.277304011  0.576895356
## EPL_UNINSUR     0.0378656738    0.226629758  0.236725641  0.393687432
## EPL_NOINT       0.0652935423    0.194521265  0.191434947  0.304220976
## SPL_SVM_DOM2    0.0591806242    0.299291164  0.302874206  0.580606654
## RPL_SVM_DOM2    0.0539645839    0.303993507  0.309493925  0.586961557
## EPL_AGE65       0.0425666246   -0.134101060 -0.137261455 -0.525643173
## EPL_AGE17       0.0118783632    0.117644341  0.119380421  0.426489479
## EPL_DISABL      0.0105524321   -0.183910890 -0.191741571  0.021016797
## EPL_LIMENG      0.0375221435    0.164073404  0.162322810  0.468508959
## SPL_SVM_DOM3    0.0586888434   -0.059286009 -0.065397035  0.110824847
## RPL_SVM_DOM3    0.0341289134   -0.044642663 -0.049082954  0.128580972
## EPL_MOBILE      0.0647012146    0.084567739  0.076730275 -0.007338135
## EPL_GROUPQ      0.0296882088    0.099773360  0.096632653 -0.043178296
## SPL_SVM_DOM4    0.0570643835    0.127176719  0.120657249 -0.040812158
## RPL_SVM_DOM4    0.0558535397    0.128439312  0.120282191 -0.050632167
## SPL_SVM         0.0814465772    0.267883976  0.267321405  0.513686732
## RPL_SVM         0.0696453371    0.280447259  0.283514025  0.528014577
## F_BPHIGH       -0.0169046047    0.084519883  0.085856035 -0.016153863
## F_ASTHMA        0.0404563112    0.282885936  0.288812874  0.511140317
## F_CANCER       -0.0313723573   -0.089170207 -0.079654943 -0.479589132
## F_MHLTH         0.0250564775    0.171654168  0.169155049  0.398603538
## F_DIABETES      0.0465044957    0.303279950  0.310004156  0.437247157
## F_HVM           0.0234354368    0.272414090  0.278345955  0.342229981
## RPL_HVM         0.0234354368    0.272414090  0.278345955  0.342229981
## E_OZONE        -0.0060693668   -0.303040127 -0.313043063 -0.367945693
## E_PM           -0.1165280999    0.484973211  0.524561962  0.077584569
## E_DSLPM        -0.0202523926    0.197081966  0.200901657  0.548460403
## E_TOTCR         0.0768487032    0.265615331  0.253351213  0.597540232
## E_NPL                     NA             NA           NA           NA
## E_TRI           0.0818575508    0.179911116  0.174926106  0.296043510
## E_TSD          -0.0052781575    0.005817259  0.006075548  0.030023915
## E_RMP           0.1817841454    0.139242204  0.112633307 -0.045751775
## E_COAL                    NA             NA           NA           NA
## E_LEAD                    NA             NA           NA           NA
## E_PARK          0.0072409635    0.550009416  0.527299069  0.390603779
## E_HOUAGE       -0.0069078029    0.071920948  0.072984866 -0.107718561
## E_WLKIND       -0.0880445530    0.023900072  0.028160339 -0.008387480
## E_RAIL         -0.0133328717    0.887423579  0.932417418  0.222472698
## E_ROAD         -0.6107721479    0.192047816  0.230782285  0.217957780
## E_AIRPRT        0.6967118001    0.257784521  0.142780963  0.032995082
## E_IMPWTR        0.0363838780    0.350744054  0.330345580  0.964509935
## EP_MINRTY       0.0520008610    0.244476051  0.246800228  0.603605225
## EP_POV200       0.0608058506    0.235178001  0.231240594  0.528188603
## EP_NOHSDP       0.0181648728    0.213231828  0.214361551  0.501938221
## EP_UNEMP        0.0413020173    0.145618396  0.149535452  0.255942547
## EP_RENTER       0.0033093970    0.291193863  0.297564798  0.483602366
## EP_HOUBDN       0.0226024972    0.266415927  0.273790985  0.505527053
## EP_UNINSUR      0.0252307672    0.206227649  0.215562806  0.357324485
## EP_NOINT        0.0610101970    0.163394217  0.157735648  0.266850911
## EP_AGE65        0.0238455619   -0.092106544 -0.092902584 -0.528172451
## EP_AGE17       -0.0002123141    0.099111746  0.102391020  0.368233238
## EP_DISABL       0.0003691784   -0.160061711 -0.166341955  0.017331799
## EP_LIMENG       0.0180877225    0.210605591  0.214800524  0.466531748
## EP_MOBILE       0.0837409606    0.073087897  0.061423859 -0.083952706
## EP_GROUPQ       0.0169751492    0.012904739  0.006637975 -0.138469318
## EP_BPHIGH      -0.0193583308    0.110904273  0.116794798  0.032383417
## EP_ASTHMA       0.0039535934    0.214213706  0.217379961  0.357064552
## EP_CANCER      -0.0583653239   -0.200402409 -0.196688790 -0.624860386
## EP_MHLTH        0.0434666764    0.219773612  0.216282439  0.504304851
## EP_DIABETES     0.0280416308    0.195496359  0.196072548  0.374117671
## EPL_BPHIGH     -0.0141298341    0.132268438  0.139145500  0.066083891
## EPL_ASTHMA      0.0181652837    0.260935624  0.264348021  0.520938569
## EPL_CANCER     -0.0564630464   -0.223343298 -0.220362948 -0.627877351
## EPL_DIABETES    0.0418593350    0.257083843  0.259911802  0.498724943
## EPL_MHLTH       0.0408311631    0.242488645  0.240112578  0.562673191
##                SPL_EBM_THEME5 RPL_EBM_DOM5      SPL_EBM      RPL_EBM
## E_TOTPOP          0.038561491  0.038492890  0.108808769  0.114522869
## M_TOTPOP          0.052456103  0.052380312  0.084001096  0.080443471
## E_DAYPOP         -0.021906638 -0.021988926  0.215084797  0.147715784
## SPL_EJI           0.513525204  0.513531704  0.341508796  0.389062710
## RPL_EJI           0.521641736  0.521661366  0.368912381  0.429100559
## SPL_SER           0.587422618  0.587431882  0.533243815  0.571784499
## RPL_SER           0.591646197  0.591668966  0.530840615  0.589087671
## EPL_OZONE        -0.311642649 -0.311708513 -0.111793693 -0.136051657
## EPL_PM            0.067437483  0.067749081  0.114761735  0.175762632
## EPL_DSLPM         0.670209666  0.670262476  0.287073460  0.365453091
## EPL_TOTCR         0.656314273  0.656292513  0.351539553  0.411997318
## SPL_EBM_THEME1    0.435784578  0.435806651  0.315671680  0.386721353
## RPL_EBM_DOM1      0.414863221  0.414885111  0.301810480  0.368554789
## EPL_NPL                    NA           NA           NA           NA
## EPL_TRI           0.261574097  0.261440115  0.438397104  0.462606186
## EPL_TSD           0.030023915  0.029970495  0.179323047  0.095583924
## EPL_RMP          -0.059233560 -0.059203726  0.424801387  0.343380872
## EPL_COAL                   NA           NA           NA           NA
## EPL_LEAD                   NA           NA           NA           NA
## SPL_EBM_THEME2    0.205666505  0.205555551  0.802500753  0.745957573
## RPL_EBM_DOM2      0.208617102  0.208500161  0.784181164  0.760511832
## EPL_PARK         -0.380246308 -0.380289441 -0.312747835 -0.413419241
## EPL_HOUAGE       -0.105457318 -0.105282314  0.298991840  0.284761977
## EPL_WLKIND        0.008389617  0.008357429  0.263738112  0.212188725
## SPL_EBM_THEME3   -0.098564395 -0.098452283  0.349459606  0.304579602
## RPL_EBM_DOM3     -0.084239776 -0.084141029  0.341447029  0.293658956
## EPL_RAIL          0.233769602  0.233847476  0.476822989  0.576991103
## EPL_ROAD          0.262814663  0.262917214  0.114101226  0.268172062
## EPL_AIRPRT        0.038677566  0.038643327  0.313061371  0.164021563
## SPL_EBM_THEME4    0.299684616  0.299765900  0.590082394  0.649635697
## RPL_EBM_DOM4      0.286260470  0.286346658  0.564927976  0.645301114
## EPL_IMPWTR        1.000000000  0.999999557  0.336408874  0.379404641
## SPL_EBM_THEME5    1.000000000  0.999999557  0.336408874  0.379404641
## RPL_EBM_DOM5      0.999999557  1.000000000  0.336405376  0.379414873
## SPL_EBM           0.336408874  0.336405376  1.000000000  0.967245811
## RPL_EBM           0.379404641  0.379414873  0.967245811  1.000000000
## EPL_MINRTY        0.594612164  0.594554336  0.179228876  0.218688845
## SPL_SVM_DOM1      0.594612164  0.594554336  0.179228876  0.218688845
## RPL_SVM_DOM1      0.594612164  0.594554336  0.179228876  0.218688845
## EPL_POV200        0.594953539  0.594949665  0.240347040  0.273213446
## EPL_NOHSDP        0.594456046  0.594438785  0.195639036  0.239916029
## EPL_UNEMP         0.265252223  0.265212546  0.114915772  0.123012560
## EPL_RENTER        0.429836124  0.429900022  0.245530620  0.276971882
## EPL_HOUBDN        0.576895356  0.576928719  0.229967298  0.260788185
## EPL_UNINSUR       0.393687432  0.393710393  0.165508416  0.179757959
## EPL_NOINT         0.304220976  0.304205445  0.069124963  0.093427650
## SPL_SVM_DOM2      0.580606654  0.580611437  0.231395655  0.264642152
## RPL_SVM_DOM2      0.586961557  0.586973208  0.240034237  0.275771174
## EPL_AGE65        -0.525643173 -0.525646596 -0.109994247 -0.141244701
## EPL_AGE17         0.426489479  0.426425515  0.061547157  0.089428511
## EPL_DISABL        0.021016797  0.021007641 -0.090879852 -0.111484047
## EPL_LIMENG        0.468508959  0.468518354  0.194320829  0.221926685
## SPL_SVM_DOM3      0.110824847  0.110772237 -0.019853443 -0.024081821
## RPL_SVM_DOM3      0.128580972  0.128525402 -0.014149764 -0.016850921
## EPL_MOBILE       -0.007338135 -0.007251370  0.056782288  0.051571026
## EPL_GROUPQ       -0.043178296 -0.043169518 -0.026278443 -0.025788765
## SPL_SVM_DOM4     -0.040812158 -0.040762403  0.004938935  0.002827738
## RPL_SVM_DOM4     -0.050632167 -0.050596206  0.007071500  0.004473238
## SPL_SVM           0.513686732  0.513685136  0.188491474  0.215620909
## RPL_SVM           0.528014577  0.528021023  0.203514852  0.234676586
## F_BPHIGH         -0.016153863 -0.016154026 -0.035091843 -0.010181763
## F_ASTHMA          0.511140317  0.511158495  0.165931657  0.202947478
## F_CANCER         -0.479589132 -0.479607615 -0.079044525 -0.103775182
## F_MHLTH           0.398603538  0.398597201  0.091064999  0.121762424
## F_DIABETES        0.437247157  0.437261004  0.151774837  0.202560469
## F_HVM             0.342229981  0.342232740  0.104951736  0.150281065
## RPL_HVM           0.342229981  0.342232740  0.104951736  0.150281065
## E_OZONE          -0.367945693 -0.368063106 -0.150902101 -0.179642260
## E_PM              0.077584569  0.077893195  0.123668093  0.186908698
## E_DSLPM           0.548460403  0.548565460  0.171530278  0.220133188
## E_TOTCR           0.597540232  0.597522518  0.307451347  0.344531263
## E_NPL                      NA           NA           NA           NA
## E_TRI             0.296043510  0.295915035  0.440430505  0.458185312
## E_TSD             0.030023915  0.029970495  0.179323047  0.095583924
## E_RMP            -0.045751775 -0.045715330  0.354122288  0.290561894
## E_COAL                     NA           NA           NA           NA
## E_LEAD                     NA           NA           NA           NA
## E_PARK            0.390603779  0.390650918  0.315631028  0.419074057
## E_HOUAGE         -0.107718561 -0.107543088  0.298169934  0.284599175
## E_WLKIND         -0.008387480 -0.008348928 -0.265853908 -0.215599307
## E_RAIL            0.222472698  0.222557343  0.460084564  0.552527315
## E_ROAD            0.217957780  0.218058541  0.061381369  0.216303328
## E_AIRPRT          0.032995082  0.032945014  0.224415683  0.114129722
## E_IMPWTR          0.964509935  0.964568138  0.350258615  0.406407756
## EP_MINRTY         0.603605225  0.603551054  0.197019637  0.237896620
## EP_POV200         0.528188603  0.528168626  0.219969874  0.247593993
## EP_NOHSDP         0.501938221  0.501894201  0.179415734  0.221812267
## EP_UNEMP          0.255942547  0.255858372  0.115067258  0.118962964
## EP_RENTER         0.483602366  0.483671111  0.253801984  0.286299757
## EP_HOUBDN         0.505527053  0.505577575  0.207430976  0.230590189
## EP_UNINSUR        0.357324485  0.357338618  0.161244776  0.174935622
## EP_NOINT          0.266850911  0.266825739  0.070604669  0.092370725
## EP_AGE65         -0.528172451 -0.528167242 -0.100740715 -0.124100681
## EP_AGE17          0.368233238  0.368177306  0.031715828  0.061189161
## EP_DISABL         0.017331799  0.017327423 -0.024960704 -0.051686906
## EP_LIMENG         0.466531748  0.466601054  0.240161818  0.267309248
## EP_MOBILE        -0.083952706 -0.083858511  0.025830401  0.019352020
## EP_GROUPQ        -0.138469318 -0.138446061 -0.001667717 -0.018686644
## EP_BPHIGH         0.032383417  0.032343895 -0.026078824  0.004356150
## EP_ASTHMA         0.357064552  0.357028512  0.055526193  0.096253707
## EP_CANCER        -0.624860386 -0.624862314 -0.209699184 -0.229591960
## EP_MHLTH          0.504304851  0.504275398  0.170248386  0.201932345
## EP_DIABETES       0.374117671  0.374051715  0.145850895  0.186601223
## EPL_BPHIGH        0.066083891  0.066053752 -0.022415989  0.014867519
## EPL_ASTHMA        0.520938569  0.520955530  0.137600982  0.181334320
## EPL_CANCER       -0.627877351 -0.627882597 -0.198325266 -0.224213981
## EPL_DIABETES      0.498724943  0.498694668  0.187594427  0.236777264
## EPL_MHLTH         0.562673191  0.562672374  0.175795809  0.209418399
##                  EPL_MINRTY SPL_SVM_DOM1 RPL_SVM_DOM1  EPL_POV200   EPL_NOHSDP
## E_TOTPOP        0.214363665  0.214363665  0.214363665  0.20209000  0.140459315
## M_TOTPOP        0.262441712  0.262441712  0.262441712  0.24344048  0.202449846
## E_DAYPOP        0.017797712  0.017797712  0.017797712  0.10840202  0.009897681
## SPL_EJI         0.707582693  0.707582693  0.707582693  0.82897933  0.771515954
## RPL_EJI         0.711102717  0.711102717  0.711102717  0.80915176  0.763078484
## SPL_SER         0.647770758  0.647770758  0.647770758  0.86132762  0.798786606
## RPL_SER         0.640529321  0.640529321  0.640529321  0.83322652  0.785237825
## EPL_OZONE      -0.269531058 -0.269531058 -0.269531058 -0.46577561 -0.330787311
## EPL_PM          0.106143293  0.106143293  0.106143293  0.14579104  0.079814128
## EPL_DSLPM       0.465308707  0.465308707  0.465308707  0.58543784  0.540909562
## EPL_TOTCR       0.463098719  0.463098719  0.463098719  0.60825273  0.550963060
## SPL_EBM_THEME1  0.261310406  0.261310406  0.261310406  0.19019498  0.276663542
## RPL_EBM_DOM1    0.246182348  0.246182348  0.246182348  0.16984920  0.261787681
## EPL_NPL                  NA           NA           NA          NA           NA
## EPL_TRI         0.194064392  0.194064392  0.194064392  0.18635739  0.191592255
## EPL_TSD        -0.003576159 -0.003576159 -0.003576159  0.02311185 -0.013706500
## EPL_RMP        -0.101723260 -0.101723260 -0.101723260  0.03991028 -0.031488784
## EPL_COAL                 NA           NA           NA          NA           NA
## EPL_LEAD                 NA           NA           NA          NA           NA
## SPL_EBM_THEME2  0.100530258  0.100530258  0.100530258  0.21573427  0.155771639
## RPL_EBM_DOM2    0.119063218  0.119063218  0.119063218  0.23285199  0.178389995
## EPL_PARK       -0.164898023 -0.164898023 -0.164898023 -0.14663047 -0.189302928
## EPL_HOUAGE     -0.208600232 -0.208600232 -0.208600232 -0.25719687 -0.228682769
## EPL_WLKIND      0.118270447  0.118270447  0.118270447  0.06162915  0.041548493
## SPL_EBM_THEME3 -0.103686841 -0.103686841 -0.103686841 -0.16995540 -0.161922496
## RPL_EBM_DOM3   -0.085137599 -0.085137599 -0.085137599 -0.15485251 -0.160967796
## EPL_RAIL        0.225172355  0.225172355  0.225172355  0.26440381  0.212358291
## EPL_ROAD        0.033880502  0.033880502  0.033880502  0.03740926  0.098937616
## EPL_AIRPRT      0.053751345  0.053751345  0.053751345  0.05571873  0.035664296
## SPL_EBM_THEME4  0.225326787  0.225326787  0.225326787  0.26013049  0.226883858
## RPL_EBM_DOM4    0.226996274  0.226996274  0.226996274  0.25954110  0.223831984
## EPL_IMPWTR      0.594612164  0.594612164  0.594612164  0.59495354  0.594456046
## SPL_EBM_THEME5  0.594612164  0.594612164  0.594612164  0.59495354  0.594456046
## RPL_EBM_DOM5    0.594554336  0.594554336  0.594554336  0.59494966  0.594438785
## SPL_EBM         0.179228876  0.179228876  0.179228876  0.24034704  0.195639036
## RPL_EBM         0.218688845  0.218688845  0.218688845  0.27321345  0.239916029
## EPL_MINRTY      1.000000000  1.000000000  1.000000000  0.69662372  0.673881206
## SPL_SVM_DOM1    1.000000000  1.000000000  1.000000000  0.69662372  0.673881206
## RPL_SVM_DOM1    1.000000000  1.000000000  1.000000000  0.69662372  0.673881206
## EPL_POV200      0.696623718  0.696623718  0.696623718  1.00000000  0.831408763
## EPL_NOHSDP      0.673881206  0.673881206  0.673881206  0.83140876  1.000000000
## EPL_UNEMP       0.362535955  0.362535955  0.362535955  0.47869788  0.393768423
## EPL_RENTER      0.442515939  0.442515939  0.442515939  0.78536533  0.656753989
## EPL_HOUBDN      0.691474009  0.691474009  0.691474009  0.83796417  0.745653933
## EPL_UNINSUR     0.351621456  0.351621456  0.351621456  0.47155497  0.459168211
## EPL_NOINT       0.463882172  0.463882172  0.463882172  0.58718105  0.545796980
## SPL_SVM_DOM2    0.678680860  0.678680860  0.678680860  0.92313022  0.844890734
## RPL_SVM_DOM2    0.690746001  0.690746001  0.690746001  0.91795438  0.850799380
## EPL_AGE65      -0.585353391 -0.585353391 -0.585353391 -0.67875453 -0.598551503
## EPL_AGE17       0.559791905  0.559791905  0.559791905  0.73168208  0.617196950
## EPL_DISABL      0.042604176  0.042604176  0.042604176  0.14665946  0.145383315
## EPL_LIMENG      0.487361893  0.487361893  0.487361893  0.65648407  0.672470508
## SPL_SVM_DOM3    0.186522659  0.186522659  0.186522659  0.36564141  0.342555749
## RPL_SVM_DOM3    0.195527844  0.195527844  0.195527844  0.38257759  0.361549654
## EPL_MOBILE     -0.039199048 -0.039199048 -0.039199048 -0.03931265 -0.003813159
## EPL_GROUPQ     -0.019050662 -0.019050662 -0.019050662  0.11912513  0.089823502
## SPL_SVM_DOM4   -0.035490200 -0.035490200 -0.035490200  0.08364164  0.075625706
## RPL_SVM_DOM4   -0.050719570 -0.050719570 -0.050719570  0.07079732  0.069968569
## SPL_SVM         0.645745423  0.645745423  0.645745423  0.88685113  0.816713929
## RPL_SVM         0.670686731  0.670686731  0.670686731  0.89957996  0.840221459
## F_BPHIGH        0.284409899  0.284409899  0.284409899  0.09065931  0.127034051
## F_ASTHMA        0.677392740  0.677392740  0.677392740  0.67821972  0.633185374
## F_CANCER       -0.670668506 -0.670668506 -0.670668506 -0.56371004 -0.565089856
## F_MHLTH         0.500000056  0.500000056  0.500000056  0.74505176  0.648372559
## F_DIABETES      0.729598964  0.729598964  0.729598964  0.63077328  0.626594472
## F_HVM           0.610576209  0.610576209  0.610576209  0.62723811  0.586197689
## RPL_HVM         0.610576209  0.610576209  0.610576209  0.62723811  0.586197689
## E_OZONE        -0.287111691 -0.287111691 -0.287111691 -0.52555980 -0.364654890
## E_PM            0.115456224  0.115456224  0.115456224  0.15360946  0.088276924
## E_DSLPM         0.434772054  0.434772054  0.434772054  0.56163980  0.498760090
## E_TOTCR         0.458027620  0.458027620  0.458027620  0.61461211  0.538218976
## E_NPL                    NA           NA           NA          NA           NA
## E_TRI           0.229017568  0.229017568  0.229017568  0.21592552  0.226367937
## E_TSD          -0.003576159 -0.003576159 -0.003576159  0.02311185 -0.013706500
## E_RMP          -0.062782330 -0.062782330 -0.062782330  0.06414709  0.019654147
## E_COAL                   NA           NA           NA          NA           NA
## E_LEAD                   NA           NA           NA          NA           NA
## E_PARK          0.161626471  0.161626471  0.161626471  0.14422675  0.188884207
## E_HOUAGE       -0.204085839 -0.204085839 -0.204085839 -0.24908523 -0.216390227
## E_WLKIND       -0.122066268 -0.122066268 -0.122066268 -0.06702901 -0.043806095
## E_RAIL          0.224978365  0.224978365  0.224978365  0.26530986  0.215402333
## E_ROAD          0.016591350  0.016591350  0.016591350  0.01957189  0.078193343
## E_AIRPRT        0.031752797  0.031752797  0.031752797  0.05282176  0.042725974
## E_IMPWTR        0.556042000  0.556042000  0.556042000  0.53577398  0.559992501
## EP_MINRTY       0.995594477  0.995594477  0.995594477  0.69938991  0.671810519
## EP_POV200       0.622923193  0.622923193  0.622923193  0.96263653  0.789297703
## EP_NOHSDP       0.590115160  0.590115160  0.590115160  0.81515776  0.890107652
## EP_UNEMP        0.346038596  0.346038596  0.346038596  0.48533263  0.353634146
## EP_RENTER       0.511884310  0.511884310  0.511884310  0.85533997  0.705953703
## EP_HOUBDN       0.580522652  0.580522652  0.580522652  0.80250224  0.654247660
## EP_UNINSUR      0.317269945  0.317269945  0.317269945  0.44665523  0.426184178
## EP_NOINT        0.433111048  0.433111048  0.433111048  0.55550564  0.514806814
## EP_AGE65       -0.590787541 -0.590787541 -0.590787541 -0.63219898 -0.578548447
## EP_AGE17        0.528419225  0.528419225  0.528419225  0.65975683  0.578912918
## EP_DISABL      -0.025182863 -0.025182863 -0.025182863  0.14128207  0.094571460
## EP_LIMENG       0.441997026  0.441997026  0.441997026  0.65725930  0.622966778
## EP_MOBILE      -0.050243001 -0.050243001 -0.050243001 -0.08988080 -0.036703027
## EP_GROUPQ      -0.261281882 -0.261281882 -0.261281882 -0.05723070 -0.080854419
## EP_BPHIGH       0.333833539  0.333833539  0.333833539  0.13959437  0.169073375
## EP_ASTHMA       0.651027883  0.651027883  0.651027883  0.64729779  0.612624578
## EP_CANCER      -0.703562622 -0.703562622 -0.703562622 -0.72975481 -0.644241120
## EP_MHLTH        0.625399785  0.625399785  0.625399785  0.87027912  0.789572011
## EP_DIABETES     0.627575221  0.627575221  0.627575221  0.69063138  0.640517316
## EPL_BPHIGH      0.378010365  0.378010365  0.378010365  0.17514835  0.208937173
## EPL_ASTHMA      0.765834831  0.765834831  0.765834831  0.73638934  0.730160830
## EPL_CANCER     -0.751935026 -0.751935026 -0.751935026 -0.75268485 -0.677927071
## EPL_DIABETES    0.792426636  0.792426636  0.792426636  0.73677575  0.726339029
## EPL_MHLTH       0.663503459  0.663503459  0.663503459  0.91677950  0.827531193
##                   EPL_UNEMP  EPL_RENTER   EPL_HOUBDN   EPL_UNINSUR    EPL_NOINT
## E_TOTPOP        0.138645725  0.22473590  0.072982701  0.1754054019  0.134519359
## M_TOTPOP        0.176468974  0.24720507  0.153358948  0.2202675408  0.164350897
## E_DAYPOP        0.097365607  0.15597205  0.012455246  0.0522941030  0.064211504
## SPL_EJI         0.464080469  0.67935050  0.695002091  0.4190006061  0.649882575
## RPL_EJI         0.440172547  0.67288289  0.714209929  0.4335493785  0.613442157
## SPL_SER         0.515248585  0.74619829  0.775241966  0.5202083149  0.589659623
## RPL_SER         0.485275325  0.73429076  0.781127602  0.5026575086  0.566484137
## EPL_OZONE      -0.228971056 -0.42636902 -0.279374047 -0.2422174915 -0.319828304
## EPL_PM          0.167913548  0.21453205  0.124128729  0.2097884953  0.070246274
## EPL_DSLPM       0.263959955  0.49056981  0.462721889  0.2696207383  0.350367247
## EPL_TOTCR       0.240763697  0.48801137  0.468451472  0.2620604561  0.362551627
## SPL_EBM_THEME1  0.066084342  0.12482920  0.259412598  0.0863247721  0.051610189
## RPL_EBM_DOM1    0.056415727  0.10360466  0.247894011  0.0727031121  0.044517064
## EPL_NPL                  NA          NA           NA            NA           NA
## EPL_TRI         0.001741317  0.09568004  0.118651030  0.0366510856  0.178431465
## EPL_TSD         0.030818032  0.02929490  0.014304780  0.0776121643 -0.037523117
## EPL_RMP         0.048348153  0.10627577  0.050127733  0.0711802768 -0.127109679
## EPL_COAL                 NA          NA           NA            NA           NA
## EPL_LEAD                 NA          NA           NA            NA           NA
## SPL_EBM_THEME2  0.046485180  0.18519733  0.158061682  0.1055835074  0.059558973
## RPL_EBM_DOM2    0.044955393  0.20115914  0.170064865  0.1010228341  0.065754903
## EPL_PARK       -0.061832330 -0.14762371 -0.082098188 -0.0494791570 -0.079235641
## EPL_HOUAGE     -0.071443587 -0.14343997 -0.163768879 -0.0776280552 -0.277261166
## EPL_WLKIND      0.113160601  0.04978442  0.028635873 -0.0141648404  0.101048899
## SPL_EBM_THEME3  0.003514276 -0.09049482 -0.113268950 -0.0693675865 -0.159604957
## RPL_EBM_DOM3    0.017694135 -0.08337381 -0.100655151 -0.0691673415 -0.154224629
## EPL_RAIL        0.146113594  0.32592137  0.293414878  0.2491910032  0.200576550
## EPL_ROAD       -0.018054196  0.08194982  0.020979398  0.0007849773 -0.015349949
## EPL_AIRPRT      0.064503219  0.00487852  0.036591523  0.0378656738  0.065293542
## SPL_EBM_THEME4  0.147886665  0.30060674  0.269416481  0.2266297579  0.194521265
## RPL_EBM_DOM4    0.148959421  0.30850102  0.277304011  0.2367256409  0.191434947
## EPL_IMPWTR      0.265252223  0.42983612  0.576895356  0.3936874318  0.304220976
## SPL_EBM_THEME5  0.265252223  0.42983612  0.576895356  0.3936874318  0.304220976
## RPL_EBM_DOM5    0.265212546  0.42990002  0.576928719  0.3937103930  0.304205445
## SPL_EBM         0.114915772  0.24553062  0.229967298  0.1655084159  0.069124963
## RPL_EBM         0.123012560  0.27697188  0.260788185  0.1797579589  0.093427650
## EPL_MINRTY      0.362535955  0.44251594  0.691474009  0.3516214556  0.463882172
## SPL_SVM_DOM1    0.362535955  0.44251594  0.691474009  0.3516214556  0.463882172
## RPL_SVM_DOM1    0.362535955  0.44251594  0.691474009  0.3516214556  0.463882172
## EPL_POV200      0.478697882  0.78536533  0.837964171  0.4715549658  0.587181050
## EPL_NOHSDP      0.393768423  0.65675399  0.745653933  0.4591682109  0.545796980
## EPL_UNEMP       1.000000000  0.35243872  0.456482652  0.3506877542  0.246559548
## EPL_RENTER      0.352438719  1.00000000  0.680740661  0.4384297429  0.541880743
## EPL_HOUBDN      0.456482652  0.68074066  1.000000000  0.4704867366  0.476142325
## EPL_UNINSUR     0.350687754  0.43842974  0.470486737  1.0000000000  0.236966661
## EPL_NOINT       0.246559548  0.54188074  0.476142325  0.2369666606  1.000000000
## SPL_SVM_DOM2    0.631809319  0.81325970  0.853973869  0.6490451340  0.671244111
## RPL_SVM_DOM2    0.612446035  0.82180017  0.878701856  0.6264423359  0.653180277
## EPL_AGE65      -0.389466620 -0.59158557 -0.632217746 -0.4837254342 -0.365126834
## EPL_AGE17       0.332707533  0.56665630  0.569546767  0.3331097978  0.422948173
## EPL_DISABL      0.065010497  0.08815746  0.043659263 -0.1214214893  0.295321007
## EPL_LIMENG      0.271770883  0.58085532  0.571179405  0.3825637448  0.362887939
## SPL_SVM_DOM3    0.097543127  0.24535190  0.189032261 -0.0405088916  0.347130490
## RPL_SVM_DOM3    0.099428993  0.26461334  0.213528087  0.0153166353  0.321068285
## EPL_MOBILE     -0.033385195 -0.04087298 -0.038704892  0.0138132372  0.005202222
## EPL_GROUPQ      0.144151770  0.07169182  0.009981495  0.0668953031  0.110314945
## SPL_SVM_DOM4    0.108110788  0.04196823 -0.010207523  0.0644178983  0.097684171
## RPL_SVM_DOM4    0.106232074  0.02857991 -0.023098823  0.0398918058  0.072609009
## SPL_SVM         0.570393095  0.73700456  0.760335588  0.5336046030  0.673074030
## RPL_SVM         0.556031805  0.76150216  0.803081576  0.5367807451  0.657299992
## F_BPHIGH        0.065320622 -0.01325867  0.031189845 -0.1466114954  0.261688159
## F_ASTHMA        0.337905427  0.55484687  0.673528491  0.4406120370  0.456961344
## F_CANCER       -0.311451753 -0.40456527 -0.602610240 -0.3128274849 -0.375106691
## F_MHLTH         0.409711370  0.60162722  0.532348551  0.3498571239  0.602688703
## F_DIABETES      0.293874712  0.49154333  0.566979135  0.3066515369  0.470754173
## F_HVM           0.322707882  0.47932862  0.480178166  0.2440472823  0.565335015
## RPL_HVM         0.322707882  0.47932862  0.480178166  0.2440472823  0.565335015
## E_OZONE        -0.271428823 -0.50814598 -0.342271506 -0.2950830941 -0.334158510
## E_PM            0.173237868  0.21998038  0.131676526  0.2168689451  0.078653710
## E_DSLPM         0.256428370  0.47683706  0.448615247  0.2855458081  0.349396779
## E_TOTCR         0.249329728  0.49293273  0.470469851  0.2802386405  0.380678592
## E_NPL                    NA          NA           NA            NA           NA
## E_TRI           0.026682875  0.14910312  0.170265121  0.0857411578  0.199809079
## E_TSD           0.030818032  0.02929490  0.014304780  0.0776121643 -0.037523117
## E_RMP           0.027369736  0.13908913  0.070540769  0.0842256089 -0.125790549
## E_COAL                   NA          NA           NA            NA           NA
## E_LEAD                   NA          NA           NA            NA           NA
## E_PARK          0.060438847  0.14356343  0.081195126  0.0447384605  0.074879329
## E_HOUAGE       -0.064479283 -0.13634275 -0.156954656 -0.0727190566 -0.265405142
## E_WLKIND       -0.117531919 -0.05214146 -0.030435517  0.0087344221 -0.095453702
## E_RAIL          0.153752636  0.33560345  0.292044171  0.2463046105  0.189323769
## E_ROAD         -0.032241031  0.06879574  0.008282391  0.0012190398 -0.026211452
## E_AIRPRT        0.035555076  0.03078723  0.036161091  0.0572379056  0.065676828
## E_IMPWTR        0.249119331  0.38234120  0.536535447  0.3510801480  0.280792444
## EP_MINRTY       0.355215732  0.44719464  0.693796342  0.3653366494  0.466658065
## EP_POV200       0.459654871  0.73754173  0.749919877  0.4060815676  0.565357796
## EP_NOHSDP       0.393297009  0.62691282  0.639646639  0.3979669018  0.562089528
## EP_UNEMP        0.815656456  0.27746879  0.423839650  0.2188733051  0.238810979
## EP_RENTER       0.400236391  0.95292098  0.707977905  0.4559593512  0.536337823
## EP_HOUBDN       0.445624758  0.59971039  0.862606352  0.4023148053  0.375112786
## EP_UNINSUR      0.330618747  0.41397817  0.429272365  0.9684556792  0.220390794
## EP_NOINT        0.203427579  0.49433256  0.423174703  0.1883994317  0.960078452
## EP_AGE65       -0.345450769 -0.56602077 -0.626481160 -0.4697991892 -0.379850241
## EP_AGE17        0.271607643  0.52854004  0.501967728  0.2741928716  0.423640333
## EP_DISABL       0.110003892  0.03755459  0.058055070 -0.1063405587  0.105060550
## EP_LIMENG       0.294802811  0.57952426  0.541213094  0.4765837569  0.335051340
## EP_MOBILE      -0.063358742 -0.08019281 -0.092211466 -0.0127607343 -0.005758397
## EP_GROUPQ       0.042320270 -0.09864199 -0.104545528 -0.1561214206 -0.191838994
## EP_BPHIGH       0.088806867  0.01075523  0.053308536 -0.0461257565  0.279097669
## EP_ASTHMA       0.341807397  0.45387290  0.544902077  0.2220889269  0.597730591
## EP_CANCER      -0.418045311 -0.57406722 -0.736945509 -0.4730224550 -0.399867940
## EP_MHLTH        0.443065483  0.68902628  0.710994463  0.3904657389  0.638760428
## EP_DIABETES     0.290916631  0.48606573  0.506674390  0.2037325355  0.571126596
## EPL_BPHIGH      0.109919955  0.03818936  0.090262917 -0.0279623113  0.316224058
## EPL_ASTHMA      0.389764985  0.54166907  0.694117345  0.4056460932  0.584994223
## EPL_CANCER     -0.423922951 -0.58317066 -0.745288684 -0.4654000694 -0.449385504
## EPL_DIABETES    0.370647717  0.51907834  0.609144086  0.3576593252  0.538840167
## EPL_MHLTH       0.490190160  0.73630850  0.757725732  0.4621002761  0.652908644
##                SPL_SVM_DOM2 RPL_SVM_DOM2    EPL_AGE65    EPL_AGE17   EPL_DISABL
## E_TOTPOP         0.20704620   0.19758554 -0.173335833  0.201259174  0.005213395
## M_TOTPOP         0.26489394   0.26218269 -0.200062762  0.221374883 -0.021609776
## E_DAYPOP         0.09763715   0.09068524 -0.031674831 -0.018089749  0.039906069
## SPL_EJI          0.83360159   0.82566629 -0.477124765  0.576262009  0.216310778
## RPL_EJI          0.82041905   0.82357805 -0.465894432  0.548225297  0.152617785
## SPL_SER          0.88839827   0.89065401 -0.527332604  0.604201581  0.187419955
## RPL_SER          0.86417727   0.87767218 -0.502111558  0.562867599  0.153349626
## EPL_OZONE       -0.42928298  -0.39003921  0.391017819 -0.380379854 -0.120772288
## EPL_PM           0.19208193   0.18597369 -0.176559738  0.089100861 -0.195053460
## EPL_DSLPM        0.54533162   0.52574069 -0.461396971  0.433066178  0.076654092
## EPL_TOTCR        0.54845281   0.53318474 -0.442117405  0.445243061  0.127887267
## SPL_EBM_THEME1   0.18656350   0.21604980 -0.104919158  0.081650012 -0.087137546
## RPL_EBM_DOM1     0.16821208   0.19780801 -0.087561646  0.065691551 -0.087501348
## EPL_NPL                  NA           NA           NA           NA           NA
## EPL_TRI          0.14756382   0.13934683 -0.078087999  0.135760436  0.136819732
## EPL_TSD          0.02584510   0.02855810 -0.068599698  0.048193264  0.018085408
## EPL_RMP          0.02976749   0.04211435 -0.046898770 -0.040367791 -0.189821990
## EPL_COAL                 NA           NA           NA           NA           NA
## EPL_LEAD                 NA           NA           NA           NA           NA
## SPL_EBM_THEME2   0.17031223   0.17315809 -0.123773238  0.103102526 -0.025524276
## RPL_EBM_DOM2     0.18189209   0.18571445 -0.130091964  0.110710674 -0.030448172
## EPL_PARK        -0.13683723  -0.14245833  0.089834113 -0.106389154  0.044155930
## EPL_HOUAGE      -0.22674030  -0.21641492  0.231338787 -0.294067411 -0.076803611
## EPL_WLKIND       0.07372879   0.06835455  0.013123094  0.008792870  0.072586798
## SPL_EBM_THEME3  -0.13978887  -0.13524624  0.187412295 -0.223949671 -0.015979697
## RPL_EBM_DOM3    -0.12890741  -0.12424127  0.172071526 -0.213982220 -0.007078403
## EPL_RAIL         0.31125582   0.31932501 -0.156131089  0.128544908 -0.187116895
## EPL_ROAD         0.03256108   0.03432869 -0.077367771  0.014336195 -0.102125169
## EPL_AIRPRT       0.05918062   0.05396458  0.042566625  0.011878363  0.010552432
## SPL_EBM_THEME4   0.29929116   0.30399351 -0.134101060  0.117644341 -0.183910890
## RPL_EBM_DOM4     0.30287421   0.30949393 -0.137261455  0.119380421 -0.191741571
## EPL_IMPWTR       0.58060665   0.58696156 -0.525643173  0.426489479  0.021016797
## SPL_EBM_THEME5   0.58060665   0.58696156 -0.525643173  0.426489479  0.021016797
## RPL_EBM_DOM5     0.58061144   0.58697321 -0.525646596  0.426425515  0.021007641
## SPL_EBM          0.23139566   0.24003424 -0.109994247  0.061547157 -0.090879852
## RPL_EBM          0.26464215   0.27577117 -0.141244701  0.089428511 -0.111484047
## EPL_MINRTY       0.67868086   0.69074600 -0.585353391  0.559791905  0.042604176
## SPL_SVM_DOM1     0.67868086   0.69074600 -0.585353391  0.559791905  0.042604176
## RPL_SVM_DOM1     0.67868086   0.69074600 -0.585353391  0.559791905  0.042604176
## EPL_POV200       0.92313022   0.91795438 -0.678754533  0.731682077  0.146659459
## EPL_NOHSDP       0.84489073   0.85079938 -0.598551503  0.617196950  0.145383315
## EPL_UNEMP        0.63180932   0.61244604 -0.389466620  0.332707533  0.065010497
## EPL_RENTER       0.81325970   0.82180017 -0.591585571  0.566656298  0.088157463
## EPL_HOUBDN       0.85397387   0.87870186 -0.632217746  0.569546767  0.043659263
## EPL_UNINSUR      0.64904513   0.62644234 -0.483725434  0.333109798 -0.121421489
## EPL_NOINT        0.67124411   0.65318028 -0.365126834  0.422948173  0.295321007
## SPL_SVM_DOM2     1.00000000   0.99231556 -0.691997469  0.661324993  0.121995376
## RPL_SVM_DOM2     0.99231556   1.00000000 -0.682330440  0.641313525  0.106977992
## EPL_AGE65       -0.69199747  -0.68233044  1.000000000 -0.682597246  0.135678506
## EPL_AGE17        0.66132499   0.64131352 -0.682597246  1.000000000  0.041781319
## EPL_DISABL       0.12199538   0.10697799  0.135678506  0.041781319  1.000000000
## EPL_LIMENG       0.63961570   0.62882806 -0.494070714  0.525076486  0.073096076
## SPL_SVM_DOM3     0.28319180   0.26281983  0.122794166  0.458960461  0.732633349
## RPL_SVM_DOM3     0.30374820   0.28165121  0.054095845  0.487494383  0.675729633
## EPL_MOBILE      -0.02541225  -0.02383217  0.025112884 -0.063741603 -0.019266015
## EPL_GROUPQ       0.12044550   0.09119462 -0.023383819  0.065420147  0.089190089
## SPL_SVM_DOM4     0.09153858   0.06707567 -0.007961078  0.025440306  0.067566561
## RPL_SVM_DOM4     0.07325454   0.04854426  0.009596655  0.016733101  0.062364911
## SPL_SVM          0.92418943   0.90713127 -0.549192770  0.683621165  0.311194421
## RPL_SVM          0.93545071   0.93319538 -0.562276357  0.676301228  0.271435433
## F_BPHIGH         0.07668120   0.07619081  0.140232064 -0.016753641  0.244571310
## F_ASTHMA         0.69506215   0.71820985 -0.530648939  0.454464076  0.051662260
## F_CANCER        -0.57559738  -0.59805867  0.611544003 -0.429496517 -0.019503422
## F_MHLTH          0.72365858   0.68314065 -0.579400336  0.613893156  0.165598424
## F_DIABETES       0.62199804   0.62461077 -0.420129382  0.446673701  0.038750921
## F_HVM            0.61158303   0.59654736 -0.333841423  0.431332455  0.195777680
## RPL_HVM          0.61158303   0.59654736 -0.333841423  0.431332455  0.195777680
## E_OZONE         -0.49364416  -0.45467548  0.432784901 -0.417337318 -0.089457715
## E_PM             0.20141739   0.19518013 -0.182323388  0.094024997 -0.193527592
## E_DSLPM          0.53076894   0.50812092 -0.457843341  0.425594349  0.090641095
## E_TOTCR          0.55831876   0.53889020 -0.452012996  0.454572888  0.160049943
## E_NPL                    NA           NA           NA           NA           NA
## E_TRI            0.19556154   0.18885603 -0.111922968  0.162220280  0.125937230
## E_TSD            0.02584510   0.02855810 -0.068599698  0.048193264  0.018085408
## E_RMP            0.04964533   0.06392701 -0.046459241  0.002824652 -0.178495616
## E_COAL                   NA           NA           NA           NA           NA
## E_LEAD                   NA           NA           NA           NA           NA
## E_PARK           0.13330473   0.13845473 -0.092165331  0.102211970 -0.048113645
## E_HOUAGE        -0.21606521  -0.20636361  0.228025991 -0.288012053 -0.070055629
## E_WLKIND        -0.07697893  -0.07118086 -0.011250219 -0.011435374 -0.072213088
## E_RAIL           0.31208529   0.31887617 -0.159355556  0.130579210 -0.194513651
## E_ROAD           0.01626084   0.01789865 -0.073621876  0.002841175 -0.105047266
## E_AIRPRT         0.06136602   0.05126683 -0.040039180  0.027102960 -0.059038197
## E_IMPWTR         0.53111185   0.54147835 -0.476914356  0.376663969  0.029561835
## EP_MINRTY        0.68193893   0.69471889 -0.587461715  0.560806123  0.029878577
## EP_POV200        0.86532033   0.84541812 -0.627577679  0.725615033  0.173197283
## EP_NOHSDP        0.79451210   0.76958656 -0.532000464  0.634897153  0.191022349
## EP_UNEMP         0.54208068   0.50670748 -0.353566889  0.351648183  0.152716853
## EP_RENTER        0.84678590   0.83889705 -0.654070040  0.618614027  0.091150194
## EP_HOUBDN        0.76269059   0.76277645 -0.567489242  0.557226689  0.029323506
## EP_UNINSUR       0.61414230   0.58084572 -0.475720654  0.334798214 -0.126125233
## EP_NOINT         0.61661332   0.58972671 -0.295302858  0.375961799  0.325399859
## EP_AGE65        -0.66361183  -0.66248150  0.939372902 -0.654215416  0.138541074
## EP_AGE17         0.59712067   0.57936954 -0.638226173  0.954467634  0.006611514
## EP_DISABL        0.08375585   0.07278448  0.187332739 -0.068795605  0.814216441
## EP_LIMENG        0.64708261   0.62373262 -0.504651099  0.492988342 -0.073997968
## EP_MOBILE       -0.07058019  -0.06823345  0.053404356 -0.069919112  0.010664599
## EP_GROUPQ       -0.11711812  -0.12454113  0.165910330 -0.235343454  0.034324525
## EP_BPHIGH        0.13097362   0.13053612  0.181721223  0.043825068  0.272947579
## EP_ASTHMA        0.63183706   0.62650407 -0.458382794  0.518905754  0.152228816
## EP_CANCER       -0.73455797  -0.73815197  0.820069046 -0.604051891  0.097991449
## EP_MHLTH         0.83732123   0.81570491 -0.668535551  0.691473844  0.136223187
## EP_DIABETES      0.62545825   0.61256572 -0.288292716  0.488434639  0.250845085
## EPL_BPHIGH       0.17062134   0.16805200  0.138775189  0.075881806  0.272477293
## EPL_ASTHMA       0.75270202   0.76241949 -0.573966503  0.541765192  0.111922887
## EPL_CANCER      -0.75683361  -0.75925826  0.834895999 -0.623898814  0.071074787
## EPL_DIABETES     0.71278346   0.71186314 -0.405820812  0.547074528  0.202413642
## EPL_MHLTH        0.89621757   0.87668241 -0.719345184  0.722444400  0.147858095
##                  EPL_LIMENG SPL_SVM_DOM3  RPL_SVM_DOM3   EPL_MOBILE
## E_TOTPOP        0.173162374  0.087442846  0.1210377318 -0.058135856
## M_TOTPOP        0.158109944  0.062528891  0.0955563686 -0.043297846
## E_DAYPOP        0.045422018  0.001981533  0.0142199198 -0.024719933
## SPL_EJI         0.500768878  0.382362295  0.3818456047 -0.002016489
## RPL_EJI         0.491335408  0.329428704  0.3345174145 -0.008480951
## SPL_SER         0.640503691  0.397857854  0.4121305453  0.057802084
## RPL_SER         0.614024166  0.356396027  0.3716423530  0.045622423
## EPL_OZONE      -0.435571912 -0.220280871 -0.2534842737  0.049824813
## EPL_PM          0.072104341 -0.149312707 -0.1145880103  0.073574363
## EPL_DSLPM       0.578633620  0.232062481  0.2553106903 -0.058452436
## EPL_TOTCR       0.546599863  0.273882492  0.2945228229 -0.055373843
## SPL_EBM_THEME1  0.141141176 -0.017038984 -0.0216471421  0.023359316
## RPL_EBM_DOM1    0.138467818 -0.017553714 -0.0233856091  0.015466929
## EPL_NPL                  NA           NA            NA           NA
## EPL_TRI         0.175387407  0.184164212  0.1752840132 -0.100201911
## EPL_TSD        -0.032724026 -0.014273957 -0.0004315695 -0.021683880
## EPL_RMP         0.041655651 -0.159840115 -0.1428145087  0.095797679
## EPL_COAL                 NA           NA            NA           NA
## EPL_LEAD                 NA           NA            NA           NA
## SPL_EBM_THEME2  0.199051389  0.040741676  0.0483970118 -0.018762775
## RPL_EBM_DOM2    0.235824333  0.051560915  0.0583106501 -0.022956425
## EPL_PARK       -0.120525569 -0.030296022 -0.0454401103 -0.030218104
## EPL_HOUAGE     -0.167328107 -0.154449619 -0.1623336701  0.109361782
## EPL_WLKIND     -0.010438570  0.054514143  0.0422875342  0.023395206
## SPL_EBM_THEME3 -0.139493059 -0.089017173 -0.1025298570  0.093427886
## RPL_EBM_DOM3   -0.135824397 -0.086265553 -0.1032480084  0.096149178
## EPL_RAIL        0.156889123 -0.071382665 -0.0474611199  0.060222114
## EPL_ROAD        0.045187396 -0.088975138 -0.0677111582  0.006822501
## EPL_AIRPRT      0.037522144  0.058688843  0.0341289134  0.064701215
## SPL_EBM_THEME4  0.164073404 -0.059286009 -0.0446426634  0.084567739
## RPL_EBM_DOM4    0.162322810 -0.065397035 -0.0490829536  0.076730275
## EPL_IMPWTR      0.468508959  0.110824847  0.1285809721 -0.007338135
## SPL_EBM_THEME5  0.468508959  0.110824847  0.1285809721 -0.007338135
## RPL_EBM_DOM5    0.468518354  0.110772237  0.1285254022 -0.007251370
## SPL_EBM         0.194320829 -0.019853443 -0.0141497645  0.056782288
## RPL_EBM         0.221926685 -0.024081821 -0.0168509212  0.051571026
## EPL_MINRTY      0.487361893  0.186522659  0.1955278440 -0.039199048
## SPL_SVM_DOM1    0.487361893  0.186522659  0.1955278440 -0.039199048
## RPL_SVM_DOM1    0.487361893  0.186522659  0.1955278440 -0.039199048
## EPL_POV200      0.656484071  0.365641412  0.3825775885 -0.039312653
## EPL_NOHSDP      0.672470508  0.342555749  0.3615496540 -0.003813159
## EPL_UNEMP       0.271770883  0.097543127  0.0994289931 -0.033385195
## EPL_RENTER      0.580855323  0.245351897  0.2646133399 -0.040872984
## EPL_HOUBDN      0.571179405  0.189032261  0.2135280873 -0.038704892
## EPL_UNINSUR     0.382563745 -0.040508892  0.0153166353  0.013813237
## EPL_NOINT       0.362887939  0.347130490  0.3210682846  0.005202222
## SPL_SVM_DOM2    0.639615696  0.283191799  0.3037481980 -0.025412254
## RPL_SVM_DOM2    0.628828059  0.262819828  0.2816512082 -0.023832171
## EPL_AGE65      -0.494070714  0.122794166  0.0540958453  0.025112884
## EPL_AGE17       0.525076486  0.458960461  0.4874943828 -0.063741603
## EPL_DISABL      0.073096076  0.732633349  0.6757296331 -0.019266015
## EPL_LIMENG      1.000000000  0.419036174  0.4643126530 -0.153587823
## SPL_SVM_DOM3    0.419036174  1.000000000  0.9541410842 -0.093140693
## RPL_SVM_DOM3    0.464312653  0.954141084  1.0000000000 -0.123518974
## EPL_MOBILE     -0.153587823 -0.093140693 -0.1235189738  1.000000000
## EPL_GROUPQ      0.098499932  0.117287730  0.1219537447  0.023366393
## SPL_SVM_DOM4    0.010293215  0.055886943  0.0451425996  0.506329422
## RPL_SVM_DOM4    0.002177128  0.056312122  0.0488819247  0.493143538
## SPL_SVM         0.645833459  0.514992344  0.5162535574  0.093243670
## RPL_SVM         0.660642423  0.482074393  0.4957837548  0.045651652
## F_BPHIGH       -0.172124839  0.171815771  0.1109353000  0.010026273
## F_ASTHMA        0.330597309  0.098903002  0.1068773070 -0.013661211
## F_CANCER       -0.347983256 -0.008809103 -0.0006833674 -0.070184177
## F_MHLTH         0.509992133  0.310265858  0.3294238983 -0.051265626
## F_DIABETES      0.357072591  0.174790427  0.1740489695 -0.041522203
## F_HVM           0.275523982  0.288815608  0.2756871545 -0.053042650
## RPL_HVM         0.275523982  0.288815608  0.2756871545 -0.053042650
## E_OZONE        -0.489624901 -0.218065022 -0.2493054278  0.032613014
## E_PM            0.075562175 -0.147735292 -0.1129225579  0.071503971
## E_DSLPM         0.567114795  0.233185804  0.2672223804 -0.056084389
## E_TOTCR         0.539535222  0.289889749  0.3135497767 -0.061214481
## E_NPL                    NA           NA            NA           NA
## E_TRI           0.210836448  0.185285162  0.1789934246 -0.112504775
## E_TSD          -0.032724026 -0.014273957 -0.0004315695 -0.021683880
## E_RMP           0.105834534 -0.098660790 -0.0734741903  0.059631479
## E_COAL                   NA           NA            NA           NA
## E_LEAD                   NA           NA            NA           NA
## E_PARK          0.117480690  0.022142625  0.0355558100  0.029747537
## E_HOUAGE       -0.161746848 -0.146502961 -0.1544310244  0.109873059
## E_WLKIND        0.001647109 -0.057920829 -0.0477974556 -0.018973834
## E_RAIL          0.162459932 -0.074569775 -0.0497305169  0.052081305
## E_ROAD          0.031736323 -0.101164434 -0.0760580714 -0.002509688
## E_AIRPRT        0.042387505 -0.028361478 -0.0252022895 -0.003836879
## E_IMPWTR        0.390830186  0.087214783  0.0992291658  0.001718729
## EP_MINRTY       0.474211394  0.173917982  0.1813967859 -0.029269078
## EP_POV200       0.611611713  0.398251434  0.4075569028 -0.043131435
## EP_NOHSDP       0.630593912  0.416228284  0.4135985645 -0.030065880
## EP_UNEMP        0.246581333  0.179911005  0.1817496728 -0.046898538
## EP_RENTER       0.639920566  0.260907415  0.2817772338 -0.047905474
## EP_HOUBDN       0.535687844  0.206353350  0.2418585319 -0.048412730
## EP_UNINSUR      0.384148775 -0.035611961  0.0233050422  0.002453157
## EP_NOINT        0.341412633  0.372558692  0.3332452741 -0.002906652
## EP_AGE65       -0.467399617  0.110873828  0.0615802919 -0.002757004
## EP_AGE17        0.486689483  0.423543425  0.4475350609 -0.042191453
## EP_DISABL      -0.029801112  0.544619270  0.4864873628 -0.023252027
## EP_LIMENG       0.813643588  0.238731110  0.2732918495 -0.012481537
## EP_MOBILE      -0.192733406 -0.073302720 -0.1009311602  0.882935982
## EP_GROUPQ      -0.156626105 -0.089941117 -0.0768505590 -0.023889929
## EP_BPHIGH      -0.124388422  0.280079929  0.2528779248 -0.036698905
## EP_ASTHMA       0.214571425  0.218292851  0.2173019491  0.008428629
## EP_CANCER      -0.513998319  0.022681463 -0.0002464860 -0.026708583
## EP_MHLTH        0.542892799  0.298106481  0.3086577924 -0.022930296
## EP_DIABETES     0.395586067  0.437492693  0.4198578430 -0.040634871
## EPL_BPHIGH     -0.089121903  0.284749840  0.2519951341 -0.044941134
## EPL_ASTHMA      0.321456499  0.164752577  0.1673244276  0.014187515
## EPL_CANCER     -0.537177974 -0.004924552 -0.0213263260 -0.031605337
## EPL_DIABETES    0.473034395  0.394683480  0.4025460101 -0.072927793
## EPL_MHLTH       0.574049704  0.301850997  0.3162356302 -0.017140229
##                  EPL_GROUPQ SPL_SVM_DOM4 RPL_SVM_DOM4       SPL_SVM     RPL_SVM
## E_TOTPOP        0.162360961  0.111784461  0.090832819  0.2313382355  0.22986219
## M_TOTPOP        0.142615154  0.101966066  0.076581011  0.2703465318  0.27975998
## E_DAYPOP        0.246840201  0.200900154  0.209366213  0.1325771132  0.12299844
## SPL_EJI         0.216106241  0.185427617  0.171879389  0.8522251757  0.85582621
## RPL_EJI         0.202954638  0.170940510  0.158663847  0.8243085314  0.84418514
## SPL_SER         0.258643456  0.251201425  0.235905170  0.9112850927  0.93167729
## RPL_SER         0.224903295  0.216176548  0.201705773  0.8713403658  0.90737031
## EPL_OZONE      -0.168838887 -0.121412777 -0.125558982 -0.4440253424 -0.41846653
## EPL_PM          0.142184770  0.158415073  0.156038914  0.1602464042  0.17075892
## EPL_DSLPM       0.072120590  0.033791401  0.035190195  0.5285449209  0.51780551
## EPL_TOTCR       0.050936133  0.017014938  0.019256671  0.5372242996  0.52896873
## SPL_EBM_THEME1 -0.101501276 -0.076195834 -0.080011273  0.1396006859  0.16639147
## RPL_EBM_DOM1   -0.106331021 -0.084198928 -0.087103872  0.1218958535  0.14905392
## EPL_NPL                  NA           NA           NA            NA          NA
## EPL_TRI         0.034664308 -0.018814990 -0.014619463  0.1735875032  0.16095586
## EPL_TSD         0.067225816  0.047445210  0.057968757  0.0288240197  0.03405864
## EPL_RMP         0.038610325  0.079878680  0.077877025 -0.0065816569  0.01430505
## EPL_COAL                 NA           NA           NA            NA          NA
## EPL_LEAD                 NA           NA           NA            NA          NA
## SPL_EBM_THEME2  0.074900368  0.055485257  0.059269112  0.1651894500  0.17131063
## RPL_EBM_DOM2    0.056349801  0.037445146  0.038982933  0.1735208656  0.18138466
## EPL_PARK        0.033298321  0.014031060  0.013152489 -0.1231185269 -0.13090884
## EPL_HOUAGE     -0.219624928 -0.136274245 -0.134816490 -0.2705710984 -0.25461322
## EPL_WLKIND     -0.116466648 -0.089087150 -0.090308810  0.0564091016  0.04692232
## SPL_EBM_THEME3 -0.226952811 -0.150341746 -0.149956406 -0.1814372302 -0.17500097
## RPL_EBM_DOM3   -0.219195284 -0.142327270 -0.142522814 -0.1685382358 -0.16425511
## EPL_RAIL        0.111174543  0.125174888  0.123046864  0.2732236815  0.29253108
## EPL_ROAD       -0.023250846 -0.016738690 -0.005591004 -0.0005663096  0.00664797
## EPL_AIRPRT      0.029688209  0.057064383  0.055853540  0.0814465772  0.06964534
## SPL_EBM_THEME4  0.099773360  0.127176719  0.128439312  0.2678839756  0.28044726
## RPL_EBM_DOM4    0.096632653  0.120657249  0.120282191  0.2673214048  0.28351402
## EPL_IMPWTR     -0.043178296 -0.040812158 -0.050632167  0.5136867319  0.52801458
## SPL_EBM_THEME5 -0.043178296 -0.040812158 -0.050632167  0.5136867319  0.52801458
## RPL_EBM_DOM5   -0.043169518 -0.040762403 -0.050596206  0.5136851360  0.52802102
## SPL_EBM        -0.026278443  0.004938935  0.007071500  0.1884914738  0.20351485
## RPL_EBM        -0.025788765  0.002827738  0.004473238  0.2156209089  0.23467659
## EPL_MINRTY     -0.019050662 -0.035490200 -0.050719570  0.6457454226  0.67068673
## SPL_SVM_DOM1   -0.019050662 -0.035490200 -0.050719570  0.6457454226  0.67068673
## RPL_SVM_DOM1   -0.019050662 -0.035490200 -0.050719570  0.6457454226  0.67068673
## EPL_POV200      0.119125128  0.083641639  0.070797323  0.8868511254  0.89957996
## EPL_NOHSDP      0.089823502  0.075625706  0.069968569  0.8167139286  0.84022146
## EPL_UNEMP       0.144151770  0.108110788  0.106232074  0.5703930947  0.55603180
## EPL_RENTER      0.071691823  0.041968233  0.028579906  0.7370045594  0.76150216
## EPL_HOUBDN      0.009981495 -0.010207523 -0.023098823  0.7603355876  0.80308158
## EPL_UNINSUR     0.066895303  0.064417898  0.039891806  0.5336046030  0.53678075
## EPL_NOINT       0.110314945  0.097684171  0.072609009  0.6730740297  0.65729999
## SPL_SVM_DOM2    0.120445502  0.091538576  0.073254545  0.9241894307  0.93545071
## RPL_SVM_DOM2    0.091194618  0.067075671  0.048544257  0.9071312710  0.93319538
## EPL_AGE65      -0.023383819 -0.007961078  0.009596655 -0.5491927698 -0.56227636
## EPL_AGE17       0.065420147  0.025440306  0.016733101  0.6836211649  0.67630123
## EPL_DISABL      0.089190089  0.067566561  0.062364911  0.3111944209  0.27143543
## EPL_LIMENG      0.098499932  0.010293215  0.002177128  0.6458334592  0.66064242
## SPL_SVM_DOM3    0.117287730  0.055886943  0.056312122  0.5149923440  0.48207439
## RPL_SVM_DOM3    0.121953745  0.045142600  0.048881925  0.5162535574  0.49578375
## EPL_MOBILE      0.023366393  0.506329422  0.493143538  0.0932436696  0.04565165
## EPL_GROUPQ      1.000000000  0.873935786  0.871579829  0.3648761060  0.31787902
## SPL_SVM_DOM4    0.873935786  1.000000000  0.991557173  0.3600659052  0.29638935
## RPL_SVM_DOM4    0.871579829  0.991557173  1.000000000  0.3425320674  0.27753660
## SPL_SVM         0.364876106  0.360065905  0.342532067  1.0000000000  0.98427600
## RPL_SVM         0.317879020  0.296389355  0.277536600  0.9842759983  1.00000000
## F_BPHIGH       -0.002036662  0.003117740  0.003257837  0.1301662416  0.11189182
## F_ASTHMA       -0.054759304 -0.053875770 -0.067587600  0.6015296937  0.63087621
## F_CANCER        0.143528580  0.089682526  0.110511508 -0.4756931699 -0.49778969
## F_MHLTH         0.192692473  0.141287814  0.125772260  0.7185671111  0.68802731
## F_DIABETES      0.103064112  0.068713572  0.057400417  0.6046657012  0.62132706
## F_HVM           0.134181679  0.089953884  0.080751516  0.6226326579  0.61103633
## RPL_HVM         0.134181679  0.089953884  0.080751516  0.6226326579  0.61103633
## E_OZONE        -0.180658572 -0.139976081 -0.142443302 -0.4992959250 -0.47470195
## E_PM            0.145162361  0.159976899  0.157629411  0.1690470087  0.17926207
## E_DSLPM         0.076437598  0.038666431  0.037000527  0.5164070563  0.50469466
## E_TOTCR         0.048195259  0.011811159  0.013366878  0.5471384135  0.53651352
## E_NPL                    NA           NA           NA            NA          NA
## E_TRI           0.033943678 -0.025417922 -0.022674779  0.2117659998  0.20081136
## E_TSD           0.067225816  0.047445210  0.057968757  0.0288240197  0.03405864
## E_RMP          -0.024634994  0.007741737  0.001184790  0.0082529000  0.03027985
## E_COAL                   NA           NA           NA            NA          NA
## E_LEAD                   NA           NA           NA            NA          NA
## E_PARK         -0.028793340 -0.010373951 -0.008384719  0.1189766900  0.12592901
## E_HOUAGE       -0.214154297 -0.131306842 -0.129228614 -0.2585198481 -0.24281058
## E_WLKIND        0.113198957  0.088418077  0.089605764 -0.0603188086 -0.04974432
## E_RAIL          0.119223428  0.128159809  0.126936644  0.2738206614  0.29404171
## E_ROAD         -0.023696775 -0.021660406 -0.011104786 -0.0191510100 -0.01108701
## E_AIRPRT        0.065136717  0.054319955  0.063168157  0.0571996120  0.05152026
## E_IMPWTR       -0.059421448 -0.050419893 -0.059029153  0.4635354886  0.47927825
## EP_MINRTY      -0.017224233 -0.029087073 -0.045112345  0.6462673399  0.67149367
## EP_POV200       0.139053511  0.098974784  0.091404717  0.8492180952  0.84068427
## EP_NOHSDP       0.120505493  0.089327851  0.085422962  0.7943782701  0.77961141
## EP_UNEMP        0.185275699  0.137013450  0.142291351  0.5304411830  0.50355551
## EP_RENTER       0.101072539  0.063892308  0.053082257  0.7789337725  0.78816128
## EP_HOUBDN       0.101979641  0.064428138  0.060415822  0.7063044413  0.72880692
## EP_UNINSUR      0.084131027  0.073762037  0.050702065  0.5078488042  0.50363605
## EP_NOINT        0.091745748  0.077724509  0.059762992  0.6298857921  0.60170090
## EP_AGE65        0.044302306  0.036873706  0.060815807 -0.5186895805 -0.53389089
## EP_AGE17        0.016549788 -0.006236950 -0.016571443  0.6135718905  0.60138289
## EP_DISABL       0.109549864  0.083190511  0.089104000  0.2302389565  0.20086291
## EP_LIMENG       0.103568588  0.083267542  0.069374070  0.6197689716  0.62020693
## EP_MOBILE       0.013200757  0.440647294  0.424766824  0.0447907507  0.01018086
## EP_GROUPQ       0.413754449  0.345279847  0.390315100 -0.0402050926 -0.05226951
## EP_BPHIGH       0.017130351 -0.003065835  0.001416840  0.2031237787  0.19220724
## EP_ASTHMA       0.033586361  0.033068559  0.024937643  0.6069906437  0.59688353
## EP_CANCER      -0.011265996 -0.022702796 -0.004560913 -0.6228586605 -0.64110779
## EP_MHLTH        0.109037036  0.082904575  0.073070583  0.7968560882  0.78275933
## EP_DIABETES     0.040339341  0.015040109  0.008525962  0.6535362039  0.63997735
## EPL_BPHIGH      0.040202084  0.012828122  0.015261829  0.2429409034  0.22888162
## EPL_ASTHMA      0.012076571  0.017314559  0.002786967  0.6906777593  0.70219373
## EPL_CANCER     -0.008909423 -0.023050749 -0.004425679 -0.6515676033 -0.67045311
## EPL_DIABETES    0.066965253  0.022306989  0.011230891  0.7252573934  0.73525076
## EPL_MHLTH       0.131724702  0.105289385  0.092614984  0.8524028426  0.84458322
##                    F_BPHIGH    F_ASTHMA      F_CANCER      F_MHLTH  F_DIABETES
## E_TOTPOP        0.029018882  0.18988395 -0.0804588594  0.170660883  0.19450796
## M_TOTPOP        0.056477775  0.24574131 -0.1481661483  0.186228688  0.25675371
## E_DAYPOP        0.003944683  0.05531251  0.0245487686  0.037223606  0.05015995
## SPL_EJI         0.448499138  0.74142005 -0.3753282495  0.749225719  0.80803710
## RPL_EJI         0.404320683  0.76807981 -0.3600929861  0.681200328  0.82212870
## SPL_SER         0.090628517  0.60828882 -0.4589043414  0.626182031  0.60008497
## RPL_SER         0.096252164  0.61082861 -0.4511022884  0.577127342  0.59406488
## EPL_OZONE      -0.050060681 -0.20563859  0.1090961159 -0.500515703 -0.27808107
## EPL_PM          0.074811862  0.12757422  0.0013061460  0.138448710  0.15784613
## EPL_DSLPM       0.001284592  0.36947440 -0.3222534364  0.514378330  0.39490280
## EPL_TOTCR       0.029680364  0.38710368 -0.3376934813  0.484425896  0.38388035
## SPL_EBM_THEME1 -0.009427114  0.25350124 -0.2725058963  0.001398471  0.17265501
## RPL_EBM_DOM1   -0.019198914  0.24205932 -0.2622124590 -0.018807220  0.16004620
## EPL_NPL                  NA          NA            NA           NA          NA
## EPL_TRI         0.086844456  0.08335216 -0.0323846057  0.204914006  0.16968061
## EPL_TSD        -0.046449782  0.02329743 -0.0180662871 -0.060393844 -0.11349779
## EPL_RMP        -0.218926516 -0.05593676 -0.0230752279 -0.091089185 -0.13762300
## EPL_COAL                 NA          NA            NA           NA          NA
## EPL_LEAD                 NA          NA            NA           NA          NA
## SPL_EBM_THEME2 -0.106784538  0.03627596 -0.0529616014  0.112145323  0.03196673
## RPL_EBM_DOM2   -0.101641740  0.04357442 -0.0614874977  0.130527375  0.05697449
## EPL_PARK       -0.064731235 -0.18181356  0.1281443043 -0.084163326 -0.15816764
## EPL_HOUAGE     -0.042366227 -0.14059838  0.1775164148 -0.299305057 -0.13551690
## EPL_WLKIND      0.143060825  0.12450546 -0.0276231710  0.072452890  0.09805454
## SPL_EBM_THEME3  0.041498900 -0.04997995  0.1270417345 -0.192052122 -0.05901171
## RPL_EBM_DOM3    0.045201643 -0.03752566  0.1226242676 -0.180534782 -0.04262736
## EPL_RAIL        0.095166325  0.28614201 -0.0506351820  0.181023468  0.31427872
## EPL_ROAD        0.041898504  0.07493349 -0.0962142336  0.025822871  0.05639664
## EPL_AIRPRT     -0.016904605  0.04045631 -0.0313723573  0.025056477  0.04650450
## SPL_EBM_THEME4  0.084519883  0.28288594 -0.0891702070  0.171654168  0.30327995
## RPL_EBM_DOM4    0.085856035  0.28881287 -0.0796549429  0.169155049  0.31000416
## EPL_IMPWTR     -0.016153863  0.51114032 -0.4795891322  0.398603538  0.43724716
## SPL_EBM_THEME5 -0.016153863  0.51114032 -0.4795891322  0.398603538  0.43724716
## RPL_EBM_DOM5   -0.016154026  0.51115849 -0.4796076151  0.398597201  0.43726100
## SPL_EBM        -0.035091843  0.16593166 -0.0790445246  0.091064999  0.15177484
## RPL_EBM        -0.010181763  0.20294748 -0.1037751820  0.121762424  0.20256047
## EPL_MINRTY      0.284409899  0.67739274 -0.6706685058  0.500000056  0.72959896
## SPL_SVM_DOM1    0.284409899  0.67739274 -0.6706685058  0.500000056  0.72959896
## RPL_SVM_DOM1    0.284409899  0.67739274 -0.6706685058  0.500000056  0.72959896
## EPL_POV200      0.090659309  0.67821972 -0.5637100412  0.745051759  0.63077328
## EPL_NOHSDP      0.127034051  0.63318537 -0.5650898559  0.648372559  0.62659447
## EPL_UNEMP       0.065320622  0.33790543 -0.3114517529  0.409711370  0.29387471
## EPL_RENTER     -0.013258667  0.55484687 -0.4045652708  0.601627222  0.49154333
## EPL_HOUBDN      0.031189845  0.67352849 -0.6026102403  0.532348551  0.56697914
## EPL_UNINSUR    -0.146611495  0.44061204 -0.3128274849  0.349857124  0.30665154
## EPL_NOINT       0.261688159  0.45696134 -0.3751066905  0.602688703  0.47075417
## SPL_SVM_DOM2    0.076681201  0.69506215 -0.5755973767  0.723658583  0.62199804
## RPL_SVM_DOM2    0.076190808  0.71820985 -0.5980586690  0.683140651  0.62461077
## EPL_AGE65       0.140232064 -0.53064894  0.6115440030 -0.579400336 -0.42012938
## EPL_AGE17      -0.016753641  0.45446408 -0.4294965172  0.613893156  0.44667370
## EPL_DISABL      0.244571310  0.05166226 -0.0195034219  0.165598424  0.03875092
## EPL_LIMENG     -0.172124839  0.33059731 -0.3479832558  0.509992133  0.35707259
## SPL_SVM_DOM3    0.171815771  0.09890300 -0.0088091029  0.310265858  0.17479043
## RPL_SVM_DOM3    0.110935300  0.10687731 -0.0006833674  0.329423898  0.17404897
## EPL_MOBILE      0.010026273 -0.01366121 -0.0701841771 -0.051265626 -0.04152220
## EPL_GROUPQ     -0.002036662 -0.05475930  0.1435285801  0.192692473  0.10306411
## SPL_SVM_DOM4    0.003117740 -0.05387577  0.0896825263  0.141287814  0.06871357
## RPL_SVM_DOM4    0.003257837 -0.06758760  0.1105115080  0.125772260  0.05740042
## SPL_SVM         0.130166242  0.60152969 -0.4756931699  0.718567111  0.60466570
## RPL_SVM         0.111891822  0.63087621 -0.4977896869  0.688027309  0.62132706
## F_BPHIGH        1.000000000  0.23596788 -0.0474842176  0.139226569  0.37796185
## F_ASTHMA        0.235967883  1.00000000 -0.5469781012  0.462910050  0.71941444
## F_CANCER       -0.047484218 -0.54697810  1.0000000000 -0.358969442 -0.41405083
## F_MHLTH         0.139226569  0.46291005 -0.3589694422  1.000000000  0.50114507
## F_DIABETES      0.377961850  0.71941444 -0.4140508270  0.501145073  1.00000000
## F_HVM           0.662204675  0.70037554 -0.2247020698  0.697867431  0.81736896
## RPL_HVM         0.662204675  0.70037554 -0.2247020698  0.697867431  0.81736896
## E_OZONE        -0.002906493 -0.22579662  0.1422250005 -0.537722405 -0.29533328
## E_PM            0.080741770  0.13728522 -0.0020191253  0.146924570  0.16760967
## E_DSLPM         0.002814397  0.34082320 -0.2682278822  0.536770631  0.37569665
## E_TOTCR         0.053878146  0.38314555 -0.3150499462  0.515412330  0.38480008
## E_NPL                    NA          NA            NA           NA          NA
## E_TRI           0.078037091  0.10805786 -0.0688421058  0.218091373  0.18333216
## E_TSD          -0.046449782  0.02329743 -0.0180662871 -0.060393844 -0.11349779
## E_RMP          -0.180743709 -0.03273497 -0.0269002854 -0.076344335 -0.09498459
## E_COAL                   NA          NA            NA           NA          NA
## E_LEAD                   NA          NA            NA           NA          NA
## E_PARK          0.063723217  0.17898230 -0.1357227482  0.082852704  0.15570459
## E_HOUAGE       -0.036507017 -0.13327547  0.1718899258 -0.290704279 -0.12806780
## E_WLKIND       -0.146528000 -0.12835914  0.0224062502 -0.077894482 -0.09939590
## E_RAIL          0.098341344  0.28219369 -0.0385192974  0.182207596  0.31824988
## E_ROAD          0.039831150  0.05558265 -0.0765094391  0.017231686  0.03716762
## E_AIRPRT       -0.040987165  0.02729600 -0.0211670245  0.052318568  0.03137672
## E_IMPWTR        0.009547207  0.50376797 -0.4881215069  0.348904353  0.41182886
## EP_MINRTY       0.283721500  0.69346497 -0.6706951326  0.495137885  0.74000359
## EP_POV200       0.137059784  0.60603807 -0.4744254210  0.758301875  0.58940126
## EP_NOHSDP       0.153096465  0.53787372 -0.4513538484  0.731097642  0.55926620
## EP_UNEMP        0.102892018  0.28121665 -0.2643464037  0.427835848  0.28770138
## EP_RENTER       0.009928528  0.56673481 -0.4305148028  0.699318372  0.52449720
## EP_HOUBDN      -0.013136033  0.55566968 -0.4717046797  0.561064145  0.51062177
## EP_UNINSUR     -0.180993953  0.38922016 -0.2803186772  0.355622993  0.28391717
## EP_NOINT        0.304196495  0.41044224 -0.3289783239  0.592429011  0.43890459
## EP_AGE65        0.156648963 -0.51873860  0.6575043551 -0.523198605 -0.36006055
## EP_AGE17        0.010984184  0.41473151 -0.4099132016  0.570392449  0.41929935
## EP_DISABL       0.225430702  0.04101993  0.0561308363  0.094888351  0.02867425
## EP_LIMENG      -0.215586770  0.36628933 -0.3306078182  0.571819840  0.39088728
## EP_MOBILE       0.010602764 -0.04736960 -0.0664175312 -0.076963720 -0.08591939
## EP_GROUPQ       0.033513139 -0.13668929  0.2503823200 -0.058758638 -0.09778050
## EP_BPHIGH       0.789102666  0.33335202  0.0544021921  0.180349173  0.50578561
## EP_ASTHMA       0.528435094  0.65191428 -0.4533876752  0.662576571  0.63286433
## EP_CANCER       0.159279150 -0.58625767  0.7464006024 -0.559027121 -0.43521228
## EP_MHLTH        0.197894640  0.63889359 -0.5282930775  0.823586488  0.58387114
## EP_DIABETES     0.535322627  0.56800143 -0.3257184745  0.617159626  0.67622023
## EPL_BPHIGH      0.819299560  0.37651084  0.0126386614  0.238083707  0.54493521
## EPL_ASTHMA      0.399457977  0.84965612 -0.5771807060  0.645810277  0.75447764
## EPL_CANCER      0.093319992 -0.60879308  0.8038312131 -0.576789846 -0.51037864
## EPL_DIABETES    0.458065260  0.71412089 -0.4051377543  0.599972020  0.84772245
## EPL_MHLTH       0.176590441  0.69757803 -0.5655579721  0.861422527  0.64290705
##                      F_HVM     RPL_HVM       E_OZONE         E_PM      E_DSLPM
## E_TOTPOP        0.18649078  0.18649078 -0.0644917730  0.076745301  0.126101355
## M_TOTPOP        0.22526278  0.22526278 -0.0248459418  0.077646920  0.065142298
## E_DAYPOP        0.05704113  0.05704113 -0.0410353118 -0.017960560  0.024253193
## SPL_EJI         0.90399403  0.90399403 -0.4616506858  0.232085644  0.500719267
## RPL_EJI         0.87344680  0.87344680 -0.4324730571  0.273295934  0.475082311
## SPL_SER         0.57186182  0.57186182 -0.4677722449  0.221144588  0.508217706
## RPL_SER         0.55422842  0.55422842 -0.4286596930  0.245489244  0.485092499
## EPL_OZONE      -0.35995919 -0.35995919  0.9499947598 -0.411554933 -0.744807330
## EPL_PM          0.18137972  0.18137972 -0.4914561307  0.999321251  0.152086098
## EPL_DSLPM       0.38068378  0.38068378 -0.6336388541  0.130332644  0.925446841
## EPL_TOTCR       0.37771492  0.37771492 -0.5692981861 -0.022426672  0.803651881
## SPL_EBM_THEME1  0.06286709  0.06286709  0.3478314929 -0.159801207  0.107050248
## RPL_EBM_DOM1    0.04516021  0.04516021  0.3775361754 -0.181080242  0.088296157
## EPL_NPL                 NA          NA            NA           NA           NA
## EPL_TRI         0.19651104  0.19651104 -0.1000988250 -0.414482911  0.394468255
## EPL_TSD        -0.08015841 -0.08015841 -0.1045026123  0.029640999  0.023405063
## EPL_RMP        -0.19853614 -0.19853614 -0.0650635623  0.349192690 -0.284350478
## EPL_COAL                NA          NA            NA           NA           NA
## EPL_LEAD                NA          NA            NA           NA           NA
## SPL_EBM_THEME2  0.01112241  0.01112241 -0.1650730287 -0.100891064  0.143356168
## RPL_EBM_DOM2    0.02944086  0.02944086 -0.1604243399 -0.102784945  0.163830053
## EPL_PARK       -0.13837554 -0.13837554  0.1505597729 -0.252658442 -0.172596367
## EPL_HOUAGE     -0.18738579 -0.18738579  0.2145204370  0.178638640 -0.164506906
## EPL_WLKIND      0.15392101  0.15392101  0.0024282690 -0.033048118  0.002488146
## SPL_EBM_THEME3 -0.06671363 -0.06671363  0.1726570403  0.101475640 -0.133569453
## RPL_EBM_DOM3   -0.05216959 -0.05216959  0.1565821704  0.092234813 -0.125954956
## EPL_RAIL        0.29513646  0.29513646 -0.3317833860  0.567893150  0.210622405
## EPL_ROAD        0.04583056  0.04583056 -0.0726290956  0.214464170  0.097282643
## EPL_AIRPRT      0.02343544  0.02343544 -0.0060693668 -0.116528100 -0.020252393
## SPL_EBM_THEME4  0.27241409  0.27241409 -0.3030401273  0.484973211  0.197081966
## RPL_EBM_DOM4    0.27834595  0.27834595 -0.3130430632  0.524561962  0.200901657
## EPL_IMPWTR      0.34222998  0.34222998 -0.3679456932  0.077584569  0.548460403
## SPL_EBM_THEME5  0.34222998  0.34222998 -0.3679456932  0.077584569  0.548460403
## RPL_EBM_DOM5    0.34223274  0.34223274 -0.3680631062  0.077893195  0.548565460
## SPL_EBM         0.10495174  0.10495174 -0.1509021012  0.123668093  0.171530278
## RPL_EBM         0.15028107  0.15028107 -0.1796422605  0.186908698  0.220133188
## EPL_MINRTY      0.61057621  0.61057621 -0.2871116913  0.115456224  0.434772054
## SPL_SVM_DOM1    0.61057621  0.61057621 -0.2871116913  0.115456224  0.434772054
## RPL_SVM_DOM1    0.61057621  0.61057621 -0.2871116913  0.115456224  0.434772054
## EPL_POV200      0.62723811  0.62723811 -0.5255597960  0.153609461  0.561639803
## EPL_NOHSDP      0.58619769  0.58619769 -0.3646548898  0.088276924  0.498760090
## EPL_UNEMP       0.32270788  0.32270788 -0.2714288225  0.173237868  0.256428370
## EPL_RENTER      0.47932862  0.47932862 -0.5081459763  0.219980383  0.476837063
## EPL_HOUBDN      0.48017817  0.48017817 -0.3422715060  0.131676526  0.448615247
## EPL_UNINSUR     0.24404728  0.24404728 -0.2950830941  0.216868945  0.285545808
## EPL_NOINT       0.56533502  0.56533502 -0.3341585099  0.078653710  0.349396779
## SPL_SVM_DOM2    0.61158303  0.61158303 -0.4936441570  0.201417388  0.530768938
## RPL_SVM_DOM2    0.59654736  0.59654736 -0.4546754808  0.195180130  0.508120923
## EPL_AGE65      -0.33384142 -0.33384142  0.4327849014 -0.182323388 -0.457843341
## EPL_AGE17       0.43133245  0.43133245 -0.4173373175  0.094024997  0.425594349
## EPL_DISABL      0.19577768  0.19577768 -0.0894577150 -0.193527592  0.090641095
## EPL_LIMENG      0.27552398  0.27552398 -0.4896249014  0.075562175  0.567114795
## SPL_SVM_DOM3    0.28881561  0.28881561 -0.2180650218 -0.147735292  0.233185804
## RPL_SVM_DOM3    0.27568715  0.27568715 -0.2493054278 -0.112922558  0.267222380
## EPL_MOBILE     -0.05304265 -0.05304265  0.0326130138  0.071503971 -0.056084389
## EPL_GROUPQ      0.13418168  0.13418168 -0.1806585717  0.145162361  0.076437598
## SPL_SVM_DOM4    0.08995388  0.08995388 -0.1399760809  0.159976899  0.038666431
## RPL_SVM_DOM4    0.08075152  0.08075152 -0.1424433020  0.157629411  0.037000527
## SPL_SVM         0.62263266  0.62263266 -0.4992959250  0.169047009  0.516407056
## RPL_SVM         0.61103633  0.61103633 -0.4747019503  0.179262074  0.504694659
## F_BPHIGH        0.66220467  0.66220467 -0.0029064926  0.080741770  0.002814397
## F_ASTHMA        0.70037554  0.70037554 -0.2257966239  0.137285218  0.340823195
## F_CANCER       -0.22470207 -0.22470207  0.1422250005 -0.002019125 -0.268227882
## F_MHLTH         0.69786743  0.69786743 -0.5377224053  0.146924570  0.536770631
## F_DIABETES      0.81736896  0.81736896 -0.2953332806  0.167609675  0.375696651
## F_HVM           1.00000000  1.00000000 -0.3595318530  0.192804624  0.389219656
## RPL_HVM         1.00000000  1.00000000 -0.3595318530  0.192804624  0.389219656
## E_OZONE        -0.35953185 -0.35953185  1.0000000000 -0.496695889 -0.686401350
## E_PM            0.19280462  0.19280462 -0.4966958895  1.000000000  0.162276051
## E_DSLPM         0.38921966  0.38921966 -0.6864013497  0.162276051  1.000000000
## E_TOTCR         0.40568523  0.40568523 -0.6345181035 -0.021765303  0.853175495
## E_NPL                   NA          NA            NA           NA           NA
## E_TRI           0.20130629  0.20130629 -0.1219505351 -0.407703733  0.393272366
## E_TSD          -0.08015841 -0.08015841 -0.1045026123  0.029640999  0.023405063
## E_RMP          -0.15606515 -0.15606515 -0.0483476107  0.344089955 -0.266730054
## E_COAL                  NA          NA            NA           NA           NA
## E_LEAD                  NA          NA            NA           NA           NA
## E_PARK          0.13381909  0.13381909 -0.1501479097  0.247116334  0.172488307
## E_HOUAGE       -0.17801189 -0.17801189  0.2138704443  0.178208415 -0.162748579
## E_WLKIND       -0.16059301 -0.16059301  0.0017513620  0.031096357 -0.004189604
## E_RAIL          0.30012475  0.30012475 -0.3417260759  0.582616129  0.213732633
## E_ROAD          0.03399566  0.03399566 -0.0594447933  0.208791649  0.083657771
## E_AIRPRT        0.01840327  0.01840327 -0.0272928960 -0.056431360 -0.002134779
## E_IMPWTR        0.31913799  0.31913799 -0.2645983146  0.068963693  0.445374390
## EP_MINRTY       0.61658118  0.61658118 -0.2909451534  0.135365945  0.429323448
## EP_POV200       0.63888683  0.63888683 -0.5168509416  0.124334352  0.553668597
## EP_NOHSDP       0.60913202  0.60913202 -0.4765274075  0.111712897  0.538206346
## EP_UNEMP        0.33858131  0.33858131 -0.2641319733  0.132969447  0.245409162
## EP_RENTER       0.53833203  0.53833203 -0.6003978032  0.273798669  0.577471189
## EP_HOUBDN       0.45202269  0.45202269 -0.3937164338  0.203297393  0.463448943
## EP_UNINSUR      0.21707961  0.21707961 -0.3034163179  0.189278988  0.286165871
## EP_NOINT        0.56558132  0.56558132 -0.3200839719  0.056686675  0.335302884
## EP_AGE65       -0.26809948 -0.26809948  0.3363955385 -0.117254222 -0.416027133
## EP_AGE17        0.40827300  0.40827300 -0.3590823987  0.073556787  0.392515540
## EP_DISABL       0.17031701  0.17031701 -0.0275696617 -0.181182589  0.051182846
## EP_LIMENG       0.30993985  0.30993985 -0.5572311130  0.261221989  0.625276414
## EP_MOBILE      -0.08774106 -0.08774106  0.0535782824  0.068243898 -0.095378530
## EP_GROUPQ      -0.02211772 -0.02211772  0.0006549523  0.013814858 -0.070178124
## EP_BPHIGH       0.68921327  0.68921327 -0.0109413090  0.066549469  0.067099159
## EP_ASTHMA       0.79566225  0.79566225 -0.2556639045  0.169701192  0.334944469
## EP_CANCER      -0.30538418 -0.30538418  0.3684225647 -0.136015369 -0.460212575
## EP_MHLTH        0.68648544  0.68648544 -0.4582178912  0.119058758  0.536550469
## EP_DIABETES     0.80033434  0.80033434 -0.3293617652  0.045738146  0.431828184
## EPL_BPHIGH      0.74188096  0.74188096 -0.0388586064  0.071466719  0.094373289
## EPL_ASTHMA      0.80427704  0.80427704 -0.2840245921  0.174367463  0.399415648
## EPL_CANCER     -0.35791894 -0.35791894  0.4161707737 -0.165418689 -0.463042650
## EPL_DIABETES    0.84243681  0.84243681 -0.3579335950  0.119239322  0.462744556
## EPL_MHLTH       0.72171457  0.72171457 -0.5134099758  0.160222484  0.562542702
##                     E_TOTCR E_NPL        E_TRI         E_TSD        E_RMP
## E_TOTPOP        0.093322977    NA -0.029465353 -0.0274357505  0.084025890
## M_TOTPOP        0.052597208    NA -0.058235484 -0.0302984012  0.107208668
## E_DAYPOP        0.102668101    NA  0.049779838  0.1657402457  0.152795958
## SPL_EJI         0.548922049    NA  0.299553805 -0.0149740580 -0.024655354
## RPL_EJI         0.520393571    NA  0.280634702 -0.0051302064 -0.005354821
## SPL_SER         0.581562486    NA  0.340714130  0.0644665565  0.134145270
## RPL_SER         0.557591646    NA  0.329454901  0.0479452470  0.124502377
## EPL_OZONE      -0.686464728    NA -0.202485323 -0.1566698098  0.056284089
## EPL_PM         -0.034041383    NA -0.427425385  0.0283023798  0.359569488
## EPL_DSLPM       0.881819997    NA  0.427061268  0.0317671760 -0.233639863
## EPL_TOTCR       0.967901656    NA  0.524169821  0.0783880810 -0.195483568
## SPL_EBM_THEME1  0.262457904    NA  0.200533258 -0.1123100959 -0.046674352
## RPL_EBM_DOM1    0.236445119    NA  0.196014054 -0.1134391549 -0.057373130
## EPL_NPL                  NA    NA           NA            NA           NA
## EPL_TRI         0.528749343    NA  0.963097211  0.0429512662 -0.431159469
## EPL_TSD         0.119052921    NA  0.047529497  1.0000000000  0.034149271
## EPL_RMP        -0.230738860    NA -0.386900033  0.1202062973  0.896123297
## EPL_COAL                 NA    NA           NA            NA           NA
## EPL_LEAD                 NA    NA           NA            NA           NA
## SPL_EBM_THEME2  0.330446706    NA  0.606864672  0.2785097475  0.343122863
## RPL_EBM_DOM2    0.337265448    NA  0.629408560  0.1394121791  0.345204762
## EPL_PARK       -0.290855426    NA -0.103912935 -0.0042357890 -0.027119845
## EPL_HOUAGE     -0.282768918    NA -0.266071222 -0.1222079044  0.168090693
## EPL_WLKIND      0.008841115    NA -0.074855580  0.0787410995  0.028520434
## SPL_EBM_THEME3 -0.226759788    NA -0.247959001 -0.0499299621  0.140762129
## RPL_EBM_DOM3   -0.214063718    NA -0.238715020 -0.0606446221  0.140731038
## EPL_RAIL        0.223581989    NA  0.168872651  0.0121470949  0.073597238
## EPL_ROAD        0.126203881    NA -0.004456369 -0.0051296945 -0.038257816
## EPL_AIRPRT      0.076848703    NA  0.081857551 -0.0052781575  0.181784145
## SPL_EBM_THEME4  0.265615331    NA  0.179911116  0.0058172590  0.139242204
## RPL_EBM_DOM4    0.253351213    NA  0.174926106  0.0060755477  0.112633307
## EPL_IMPWTR      0.597540232    NA  0.296043510  0.0300239152 -0.045751775
## SPL_EBM_THEME5  0.597540232    NA  0.296043510  0.0300239152 -0.045751775
## RPL_EBM_DOM5    0.597522518    NA  0.295915035  0.0299704952 -0.045715330
## SPL_EBM         0.307451347    NA  0.440430505  0.1793230472  0.354122288
## RPL_EBM         0.344531263    NA  0.458185312  0.0955839242  0.290561894
## EPL_MINRTY      0.458027620    NA  0.229017568 -0.0035761585 -0.062782330
## SPL_SVM_DOM1    0.458027620    NA  0.229017568 -0.0035761585 -0.062782330
## RPL_SVM_DOM1    0.458027620    NA  0.229017568 -0.0035761585 -0.062782330
## EPL_POV200      0.614612108    NA  0.215925520  0.0231118450  0.064147089
## EPL_NOHSDP      0.538218976    NA  0.226367937 -0.0137064998  0.019654147
## EPL_UNEMP       0.249329728    NA  0.026682875  0.0308180322  0.027369736
## EPL_RENTER      0.492932727    NA  0.149103115  0.0292949026  0.139089134
## EPL_HOUBDN      0.470469851    NA  0.170265121  0.0143047804  0.070540769
## EPL_UNINSUR     0.280238641    NA  0.085741158  0.0776121643  0.084225609
## EPL_NOINT       0.380678592    NA  0.199809079 -0.0375231166 -0.125790549
## SPL_SVM_DOM2    0.558318760    NA  0.195561539  0.0258450985  0.049645329
## RPL_SVM_DOM2    0.538890200    NA  0.188856033  0.0285580977  0.063927013
## EPL_AGE65      -0.452012996    NA -0.111922968 -0.0685996975 -0.046459241
## EPL_AGE17       0.454572888    NA  0.162220280  0.0481932640  0.002824652
## EPL_DISABL      0.160049943    NA  0.125937230  0.0180854079 -0.178495616
## EPL_LIMENG      0.539535222    NA  0.210836448 -0.0327240263  0.105834534
## SPL_SVM_DOM3    0.289889749    NA  0.185285162 -0.0142739571 -0.098660790
## RPL_SVM_DOM3    0.313549777    NA  0.178993425 -0.0004315695 -0.073474190
## EPL_MOBILE     -0.061214481    NA -0.112504775 -0.0216838799  0.059631479
## EPL_GROUPQ      0.048195259    NA  0.033943678  0.0672258159 -0.024634994
## SPL_SVM_DOM4    0.011811159    NA -0.025417922  0.0474452102  0.007741737
## RPL_SVM_DOM4    0.013366878    NA -0.022674779  0.0579687572  0.001184790
## SPL_SVM         0.547138413    NA  0.211766000  0.0288240197  0.008252900
## RPL_SVM         0.536513519    NA  0.200811365  0.0340586354  0.030279853
## F_BPHIGH        0.053878146    NA  0.078037091 -0.0464497820 -0.180743709
## F_ASTHMA        0.383145550    NA  0.108057860  0.0232974312 -0.032734970
## F_CANCER       -0.315049946    NA -0.068842106 -0.0180662871 -0.026900285
## F_MHLTH         0.515412330    NA  0.218091373 -0.0603938442 -0.076344335
## F_DIABETES      0.384800078    NA  0.183332156 -0.1134977905 -0.094984585
## F_HVM           0.405685230    NA  0.201306291 -0.0801584128 -0.156065151
## RPL_HVM         0.405685230    NA  0.201306291 -0.0801584128 -0.156065151
## E_OZONE        -0.634518104    NA -0.121950535 -0.1045026123 -0.048347611
## E_PM           -0.021765303    NA -0.407703733  0.0296409991  0.344089955
## E_DSLPM         0.853175495    NA  0.393272366  0.0234050628 -0.266730054
## E_TOTCR         1.000000000    NA  0.543919611  0.1190529215 -0.225212479
## E_NPL                    NA     1           NA            NA           NA
## E_TRI           0.543919611    NA  1.000000000  0.0475294973 -0.383583853
## E_TSD           0.119052921    NA  0.047529497  1.0000000000  0.034149271
## E_RMP          -0.225212479    NA -0.383583853  0.0341492711  1.000000000
## E_COAL                   NA    NA           NA            NA           NA
## E_LEAD                   NA    NA           NA            NA           NA
## E_PARK          0.293170497    NA  0.102294766  0.0041698278  0.026697525
## E_HOUAGE       -0.281333327    NA -0.264221452 -0.1235347631  0.163771047
## E_WLKIND       -0.013131607    NA  0.070752809 -0.0815413585 -0.026913008
## E_RAIL          0.206906554    NA  0.151778824  0.0127833370  0.078709372
## E_ROAD          0.092646453    NA -0.015555368  0.0056336013 -0.052206246
## E_AIRPRT        0.055497997    NA  0.054573291 -0.0035611889  0.180050200
## E_IMPWTR        0.528682545    NA  0.265367087  0.0223267351 -0.039809431
## EP_MINRTY       0.456302190    NA  0.218911982  0.0017535280 -0.041209450
## EP_POV200       0.611149172    NA  0.230228651  0.0096792609  0.025828865
## EP_NOHSDP       0.564367687    NA  0.238959936 -0.0379191476 -0.033389171
## EP_UNEMP        0.272112537    NA  0.020956590  0.0082596533 -0.027625828
## EP_RENTER       0.575049960    NA  0.148549515  0.0285424398  0.152099146
## EP_HOUBDN       0.466289861    NA  0.094195894 -0.0078545072  0.062734056
## EP_UNINSUR      0.287414223    NA  0.102280627  0.0930861881  0.053447852
## EP_NOINT        0.375688335    NA  0.222311956 -0.0400449515 -0.140078502
## EP_AGE65       -0.406619884    NA -0.118070996 -0.0877480636 -0.053262827
## EP_AGE17        0.399903389    NA  0.146574863  0.0375029460 -0.011965409
## EP_DISABL       0.150842550    NA  0.110944309  0.0025869926 -0.142274244
## EP_LIMENG       0.501773188    NA  0.076570341 -0.0543647464  0.213566081
## EP_MOBILE      -0.105151665    NA -0.110947714 -0.0177569198  0.026745213
## EP_GROUPQ      -0.011596357    NA -0.025805224  0.0812986482 -0.041434379
## EP_BPHIGH       0.098169139    NA  0.140038830 -0.0727846350 -0.250923924
## EP_ASTHMA       0.357270970    NA  0.147105825 -0.0400409764 -0.176451154
## EP_CANCER      -0.475770473    NA -0.157067461 -0.0624671550 -0.082100267
## EP_MHLTH        0.563466839    NA  0.229193606 -0.0006942556 -0.057912276
## EP_DIABETES     0.492449837    NA  0.277342878 -0.0446842377 -0.148317377
## EPL_BPHIGH      0.124736144    NA  0.171105837 -0.0860034297 -0.280163993
## EPL_ASTHMA      0.430747858    NA  0.171740467 -0.0180318128 -0.094470649
## EPL_CANCER     -0.483951306    NA -0.149267601 -0.0503484066 -0.070497106
## EPL_DIABETES    0.502676740    NA  0.279105992 -0.0344711114 -0.102161803
## EPL_MHLTH       0.586378386    NA  0.225229181  0.0085251856 -0.033777127
##                E_COAL E_LEAD       E_PARK     E_HOUAGE      E_WLKIND
## E_TOTPOP           NA     NA -0.018091031  0.027762532 -0.2751500540
## M_TOTPOP           NA     NA -0.036007141 -0.002710476 -0.2752648540
## E_DAYPOP           NA     NA -0.036973389 -0.052177602 -0.0641518142
## SPL_EJI            NA     NA  0.218104212 -0.159236163 -0.1611858193
## RPL_EJI            NA     NA  0.262178305 -0.136864795 -0.1383090834
## SPL_SER            NA     NA  0.262898630 -0.098564112 -0.1225574543
## RPL_SER            NA     NA  0.314583104 -0.092205212 -0.0911679521
## EPL_OZONE          NA     NA -0.101678695  0.241367312  0.0063469283
## EPL_PM             NA     NA  0.237439544  0.182853726  0.0265260362
## EPL_DSLPM          NA     NA  0.446641296 -0.164459625  0.0257900038
## EPL_TOTCR          NA     NA  0.458094615 -0.258226236  0.0182992622
## SPL_EBM_THEME1     NA     NA  0.522622861  0.091533612  0.0432316209
## RPL_EBM_DOM1       NA     NA  0.486470510  0.101469322  0.0343771653
## EPL_NPL            NA     NA           NA           NA            NA
## EPL_TRI            NA     NA  0.115558251 -0.251081371  0.0563431990
## EPL_TSD            NA     NA  0.004169828 -0.123534763 -0.0815413585
## EPL_RMP            NA     NA  0.031696072  0.148042179 -0.0167060453
## EPL_COAL           NA     NA           NA           NA            NA
## EPL_LEAD           NA     NA           NA           NA            NA
## SPL_EBM_THEME2     NA     NA  0.138226307 -0.133727587  0.0289924616
## RPL_EBM_DOM2       NA     NA  0.150429971 -0.124291225  0.0495021940
## EPL_PARK           NA     NA -0.997432555 -0.007147892 -0.0901295345
## EPL_HOUAGE         NA     NA  0.012842041  0.997562969 -0.1566066814
## EPL_WLKIND         NA     NA -0.089382230  0.158256135 -0.9953438933
## SPL_EBM_THEME3     NA     NA -0.100204590  0.838897768 -0.6630361723
## RPL_EBM_DOM3       NA     NA -0.108892696  0.781416145 -0.6921184423
## EPL_RAIL           NA     NA  0.403688457  0.032401785  0.0525332681
## EPL_ROAD           NA     NA  0.644229595  0.148252840  0.0733929824
## EPL_AIRPRT         NA     NA  0.007240964 -0.006907803 -0.0880445530
## SPL_EBM_THEME4     NA     NA  0.550009416  0.071920948  0.0239000720
## RPL_EBM_DOM4       NA     NA  0.527299069  0.072984866  0.0281603395
## EPL_IMPWTR         NA     NA  0.390603779 -0.107718561 -0.0083874804
## SPL_EBM_THEME5     NA     NA  0.390603779 -0.107718561 -0.0083874804
## RPL_EBM_DOM5       NA     NA  0.390650918 -0.107543088 -0.0083489281
## SPL_EBM            NA     NA  0.315631028  0.298169934 -0.2658539079
## RPL_EBM            NA     NA  0.419074057  0.284599175 -0.2155993073
## EPL_MINRTY         NA     NA  0.161626471 -0.204085839 -0.1220662675
## SPL_SVM_DOM1       NA     NA  0.161626471 -0.204085839 -0.1220662675
## RPL_SVM_DOM1       NA     NA  0.161626471 -0.204085839 -0.1220662675
## EPL_POV200         NA     NA  0.144226754 -0.249085229 -0.0670290120
## EPL_NOHSDP         NA     NA  0.188884207 -0.216390227 -0.0438060945
## EPL_UNEMP          NA     NA  0.060438847 -0.064479283 -0.1175319193
## EPL_RENTER         NA     NA  0.143563432 -0.136342747 -0.0521414568
## EPL_HOUBDN         NA     NA  0.081195126 -0.156954656 -0.0304355166
## EPL_UNINSUR        NA     NA  0.044738461 -0.072719057  0.0087344221
## EPL_NOINT          NA     NA  0.074879329 -0.265405142 -0.0954537020
## SPL_SVM_DOM2       NA     NA  0.133304733 -0.216065206 -0.0769789331
## RPL_SVM_DOM2       NA     NA  0.138454732 -0.206363607 -0.0711808633
## EPL_AGE65          NA     NA -0.092165331  0.228025991 -0.0112502191
## EPL_AGE17          NA     NA  0.102211970 -0.288012053 -0.0114353736
## EPL_DISABL         NA     NA -0.048113645 -0.070055629 -0.0722130882
## EPL_LIMENG         NA     NA  0.117480690 -0.161746848  0.0016471087
## SPL_SVM_DOM3       NA     NA  0.022142625 -0.146502961 -0.0579208291
## RPL_SVM_DOM3       NA     NA  0.035555810 -0.154431024 -0.0477974556
## EPL_MOBILE         NA     NA  0.029747537  0.109873059 -0.0189738335
## EPL_GROUPQ         NA     NA -0.028793340 -0.214154297  0.1131989571
## SPL_SVM_DOM4       NA     NA -0.010373951 -0.131306842  0.0884180768
## RPL_SVM_DOM4       NA     NA -0.008384719 -0.129228614  0.0896057643
## SPL_SVM            NA     NA  0.118976690 -0.258519848 -0.0603188086
## RPL_SVM            NA     NA  0.125929006 -0.242810583 -0.0497443196
## F_BPHIGH           NA     NA  0.063723217 -0.036507017 -0.1465279996
## F_ASTHMA           NA     NA  0.178982298 -0.133275474 -0.1283591416
## F_CANCER           NA     NA -0.135722748  0.171889926  0.0224062502
## F_MHLTH            NA     NA  0.082852704 -0.290704279 -0.0778944818
## F_DIABETES         NA     NA  0.155704592 -0.128067804 -0.0993958993
## F_HVM              NA     NA  0.133819085 -0.178011892 -0.1605930104
## RPL_HVM            NA     NA  0.133819085 -0.178011892 -0.1605930104
## E_OZONE            NA     NA -0.150147910  0.213870444  0.0017513620
## E_PM               NA     NA  0.247116334  0.178208415  0.0310963569
## E_DSLPM            NA     NA  0.172488307 -0.162748579 -0.0041896037
## E_TOTCR            NA     NA  0.293170497 -0.281333327 -0.0131316070
## E_NPL              NA     NA           NA           NA            NA
## E_TRI              NA     NA  0.102294766 -0.264221452  0.0707528090
## E_TSD              NA     NA  0.004169828 -0.123534763 -0.0815413585
## E_RMP              NA     NA  0.026697525  0.163771047 -0.0269130077
## E_COAL              1     NA           NA           NA            NA
## E_LEAD             NA      1           NA           NA            NA
## E_PARK             NA     NA  1.000000000  0.010097885  0.0890920478
## E_HOUAGE           NA     NA  0.010097885  1.000000000 -0.1595274587
## E_WLKIND           NA     NA  0.089092048 -0.159527459  1.0000000000
## E_RAIL             NA     NA  0.370926232  0.052862018  0.0640701969
## E_ROAD             NA     NA  0.553927127  0.146947908  0.0720027104
## E_AIRPRT           NA     NA  0.004885500 -0.005192267 -0.0160546079
## E_IMPWTR           NA     NA  0.514945430 -0.081072237  0.0003961643
## EP_MINRTY          NA     NA  0.174900225 -0.197085830 -0.1228292699
## EP_POV200          NA     NA  0.124065167 -0.262985508 -0.1024941867
## EP_NOHSDP          NA     NA  0.132778403 -0.207572290 -0.0968197460
## EP_UNEMP           NA     NA  0.066557412 -0.064144904 -0.1316541482
## EP_RENTER          NA     NA  0.139101194 -0.161010609 -0.0730249182
## EP_HOUBDN          NA     NA  0.097551511 -0.136289318 -0.0474805539
## EP_UNINSUR         NA     NA  0.046437992 -0.058283821 -0.0097354660
## EP_NOINT           NA     NA  0.070289565 -0.253295521 -0.1328642265
## EP_AGE65           NA     NA -0.065564646  0.218916248 -0.0494098577
## EP_AGE17           NA     NA  0.088669901 -0.280812713 -0.0364069245
## EP_DISABL          NA     NA -0.035502946 -0.004382962 -0.0987765550
## EP_LIMENG          NA     NA  0.100437363 -0.032847291 -0.0161535954
## EP_MOBILE          NA     NA  0.024360245  0.110953861  0.0039022652
## EP_GROUPQ          NA     NA -0.062427139 -0.041930902  0.0170798704
## EP_BPHIGH          NA     NA  0.081805948 -0.034089585 -0.2052365868
## EP_ASTHMA          NA     NA  0.119067213 -0.227030924 -0.1831507460
## EP_CANCER          NA     NA -0.111592327  0.217404733 -0.0405961420
## EP_MHLTH           NA     NA  0.111815320 -0.269612132 -0.1075181900
## EP_DIABETES        NA     NA  0.134668041 -0.212234434 -0.2146196585
## EPL_BPHIGH         NA     NA  0.088375857 -0.057226132 -0.1937361736
## EPL_ASTHMA         NA     NA  0.156692212 -0.202729943 -0.1214098872
## EPL_CANCER         NA     NA -0.132620969  0.231142187 -0.0139639427
## EPL_DIABETES       NA     NA  0.192718830 -0.180137082 -0.1674611259
## EPL_MHLTH          NA     NA  0.125139932 -0.273423242 -0.0690850487
##                      E_RAIL       E_ROAD     E_AIRPRT      E_IMPWTR
## E_TOTPOP        0.074087957 -0.019435221  0.034347987  0.0190838127
## M_TOTPOP        0.069866006 -0.069885206  0.077884929  0.0404943628
## E_DAYPOP        0.043575517 -0.160865578  0.423779728 -0.0364608652
## SPL_EJI         0.418816771  0.057853631  0.056042715  0.4833550385
## RPL_EJI         0.489642955  0.085331807  0.048252223  0.4994514849
## SPL_SER         0.454655877  0.071480558  0.086134704  0.5563821775
## RPL_SER         0.502503469  0.119991233  0.058433021  0.5740878567
## EPL_OZONE      -0.270381925 -0.043178952 -0.010156132 -0.2024118002
## EPL_PM          0.565792846  0.204695478 -0.057491405  0.0581830287
## EPL_DSLPM       0.307862072  0.265776912  0.011710200  0.6276467354
## EPL_TOTCR       0.253592605  0.206688115  0.053634173  0.6247023342
## SPL_EBM_THEME1  0.183724485  0.293575534  0.020483127  0.5346390781
## RPL_EBM_DOM1    0.160536284  0.269314204  0.024817888  0.5111686204
## EPL_NPL                  NA           NA           NA            NA
## EPL_TRI         0.123387513 -0.011489750  0.048014694  0.2355656734
## EPL_TSD         0.012783337  0.005633601 -0.003561189  0.0223267351
## EPL_RMP         0.089576305 -0.089957477  0.161622584 -0.0465613601
## EPL_COAL                 NA           NA           NA            NA
## EPL_LEAD                 NA           NA           NA            NA
## SPL_EBM_THEME2  0.195542280 -0.085836689  0.181412698  0.1902723095
## RPL_EBM_DOM2    0.202355984 -0.045055195  0.133659634  0.1900606401
## EPL_PARK       -0.376793799 -0.528494556 -0.004962782 -0.4974012484
## EPL_HOUAGE      0.051542890  0.146240353 -0.008759735 -0.0785259312
## EPL_WLKIND     -0.068546488 -0.070213899  0.018988991  0.0011482188
## SPL_EBM_THEME3 -0.021421010  0.039863419  0.003362697 -0.0893638222
## RPL_EBM_DOM3   -0.020773412  0.009945518 -0.001980974 -0.0768111571
## EPL_RAIL        0.982560660  0.208880229 -0.007349412  0.2480418549
## EPL_ROAD        0.232124051  0.986632235 -0.253401025  0.3863714739
## EPL_AIRPRT     -0.013332872 -0.610772148  0.696711800  0.0363838780
## SPL_EBM_THEME4  0.887423579  0.192047816  0.257784521  0.3507440539
## RPL_EBM_DOM4    0.932417418  0.230782285  0.142780963  0.3303455804
## EPL_IMPWTR      0.222472698  0.217957780  0.032995082  0.9645099347
## SPL_EBM_THEME5  0.222472698  0.217957780  0.032995082  0.9645099347
## RPL_EBM_DOM5    0.222557343  0.218058541  0.032945014  0.9645681377
## SPL_EBM         0.460084564  0.061381369  0.224415683  0.3502586149
## RPL_EBM         0.552527315  0.216303328  0.114129722  0.4064077563
## EPL_MINRTY      0.224978365  0.016591350  0.031752797  0.5560419998
## SPL_SVM_DOM1    0.224978365  0.016591350  0.031752797  0.5560419998
## RPL_SVM_DOM1    0.224978365  0.016591350  0.031752797  0.5560419998
## EPL_POV200      0.265309855  0.019571889  0.052821764  0.5357739836
## EPL_NOHSDP      0.215402333  0.078193343  0.042725974  0.5599925009
## EPL_UNEMP       0.153752636 -0.032241031  0.035555076  0.2491193305
## EPL_RENTER      0.335603450  0.068795742  0.030787229  0.3823412044
## EPL_HOUBDN      0.292044171  0.008282391  0.036161091  0.5365354468
## EPL_UNINSUR     0.246304611  0.001219040  0.057237906  0.3510801480
## EPL_NOINT       0.189323769 -0.026211452  0.065676828  0.2807924438
## SPL_SVM_DOM2    0.312085288  0.016260844  0.061366016  0.5311118459
## RPL_SVM_DOM2    0.318876174  0.017898654  0.051266833  0.5414783521
## EPL_AGE65      -0.159355556 -0.073621876 -0.040039180 -0.4769143563
## EPL_AGE17       0.130579210  0.002841175  0.027102960  0.3766639686
## EPL_DISABL     -0.194513651 -0.105047266 -0.059038197  0.0295618348
## EPL_LIMENG      0.162459932  0.031736323  0.042387505  0.3908301863
## SPL_SVM_DOM3   -0.074569775 -0.101164434 -0.028361478  0.0872147827
## RPL_SVM_DOM3   -0.049730517 -0.076058071 -0.025202289  0.0992291658
## EPL_MOBILE      0.052081305 -0.002509688 -0.003836879  0.0017187287
## EPL_GROUPQ      0.119223428 -0.023696775  0.065136717 -0.0594214485
## SPL_SVM_DOM4    0.128159809 -0.021660406  0.054319955 -0.0504198931
## RPL_SVM_DOM4    0.126936644 -0.011104786  0.063168157 -0.0590291529
## SPL_SVM         0.273820661 -0.019151010  0.057199612  0.4635354886
## RPL_SVM         0.294041706 -0.011087012  0.051520261  0.4792782504
## F_BPHIGH        0.098341344  0.039831150 -0.040987165  0.0095472071
## F_ASTHMA        0.282193692  0.055582646  0.027295996  0.5037679742
## F_CANCER       -0.038519297 -0.076509439 -0.021167024 -0.4881215069
## F_MHLTH         0.182207596  0.017231686  0.052318568  0.3489043528
## F_DIABETES      0.318249882  0.037167616  0.031376724  0.4118288563
## F_HVM           0.300124746  0.033995658  0.018403273  0.3191379935
## RPL_HVM         0.300124746  0.033995658  0.018403273  0.3191379935
## E_OZONE        -0.341726076 -0.059444793 -0.027292896 -0.2645983146
## E_PM            0.582616129  0.208791649 -0.056431360  0.0689636932
## E_DSLPM         0.213732633  0.083657771 -0.002134779  0.4453743903
## E_TOTCR         0.206906554  0.092646453  0.055497997  0.5286825454
## E_NPL                    NA           NA           NA            NA
## E_TRI           0.151778824 -0.015555368  0.054573291  0.2653670871
## E_TSD           0.012783337  0.005633601 -0.003561189  0.0223267351
## E_RMP           0.078709372 -0.052206246  0.180050200 -0.0398094308
## E_COAL                   NA           NA           NA            NA
## E_LEAD                   NA           NA           NA            NA
## E_PARK          0.370926232  0.553927127  0.004885500  0.5149454296
## E_HOUAGE        0.052862018  0.146947908 -0.005192267 -0.0810722369
## E_WLKIND        0.064070197  0.072002710 -0.016054608  0.0003961643
## E_RAIL          1.000000000  0.202077335 -0.003883841  0.2346513393
## E_ROAD          0.202077335  1.000000000 -0.291419713  0.3253870460
## E_AIRPRT       -0.003883841 -0.291419713  1.000000000  0.0257640795
## E_IMPWTR        0.234651339  0.325387046  0.025764080  1.0000000000
## EP_MINRTY       0.243811335  0.025612689  0.032602139  0.5666799195
## EP_POV200       0.240156672 -0.001654406  0.059297937  0.4693750961
## EP_NOHSDP       0.217025680  0.063786990  0.048803842  0.4502718348
## EP_UNEMP        0.160411787 -0.012198977  0.009804192  0.2461094652
## EP_RENTER       0.327602795  0.062045134  0.032920399  0.4236766631
## EP_HOUBDN       0.295377215  0.023606821  0.039677496  0.4648505047
## EP_UNINSUR      0.224737735  0.021055540  0.053033483  0.3196895994
## EP_NOINT        0.149363779 -0.012870416  0.066921450  0.2468181423
## EP_AGE65       -0.110413477 -0.041389092 -0.035967571 -0.4834718931
## EP_AGE17        0.114002270  0.004661401  0.013993217  0.3218020914
## EP_DISABL      -0.168114775 -0.078241394 -0.042340454  0.0315238045
## EP_LIMENG       0.224590499  0.061444589  0.044295334  0.3758062938
## EP_MOBILE       0.029755166 -0.019099036  0.003339210 -0.0649976609
## EP_GROUPQ       0.008218480  0.013379770  0.059383290 -0.1259261286
## EP_BPHIGH       0.145192849 -0.009674720 -0.027268319  0.0483327564
## EP_ASTHMA       0.236839403  0.034635043  0.012102655  0.3550221687
## EP_CANCER      -0.186202155 -0.030550952 -0.065874381 -0.5817662133
## EP_MHLTH        0.222357516  0.028342338  0.059769537  0.4643366152
## EP_DIABETES     0.205241857  0.005383470  0.007667649  0.3406190388
## EPL_BPHIGH      0.162640113  0.002986434 -0.026457350  0.0764583398
## EPL_ASTHMA      0.270066113  0.059461724  0.028819762  0.5137565951
## EPL_CANCER     -0.206910366 -0.046204590 -0.054624121 -0.5863327493
## EPL_DIABETES    0.258419432  0.031817876  0.025268038  0.4627063273
## EPL_MHLTH       0.246098162  0.038189646  0.059351475  0.5173792224
##                   EP_MINRTY    EP_POV200   EP_NOHSDP     EP_UNEMP    EP_RENTER
## E_TOTPOP        0.223953727  0.180564658  0.14211611  0.108648338  0.233875973
## M_TOTPOP        0.272221808  0.207334560  0.18151960  0.119303604  0.243624730
## E_DAYPOP        0.021597292  0.115987510  0.01116680  0.070496684  0.151737335
## SPL_EJI         0.715317565  0.805142223  0.75522721  0.449828229  0.728646914
## RPL_EJI         0.721970354  0.767671292  0.71461607  0.416421286  0.708230402
## SPL_SER         0.655630195  0.802046644  0.74086755  0.469446575  0.772183916
## RPL_SER         0.649215821  0.762280007  0.70002449  0.438038552  0.745425512
## EPL_OZONE      -0.270100626 -0.476235305 -0.44737009 -0.215711481 -0.526610629
## EPL_PM          0.126112071  0.116415163  0.10273188  0.127250113  0.268508283
## EPL_DSLPM       0.464074247  0.572094493  0.55716919  0.265522974  0.577875001
## EPL_TOTCR       0.463186391  0.597512110  0.55717208  0.270545758  0.560715718
## SPL_EBM_THEME1  0.267715739  0.151260337  0.14114222  0.097893937  0.106881266
## RPL_EBM_DOM1    0.251503422  0.130632898  0.12658537  0.088992811  0.085732156
## EPL_NPL                  NA           NA          NA           NA           NA
## EPL_TRI         0.184168508  0.212476186  0.21505105  0.020096240  0.102321951
## EPL_TSD         0.001753528  0.009679261 -0.03791915  0.008259653  0.028542440
## EPL_RMP        -0.078913526  0.000980073 -0.06996051  0.025005213  0.116686274
## EPL_COAL                 NA           NA          NA           NA           NA
## EPL_LEAD                 NA           NA          NA           NA           NA
## SPL_EBM_THEME2  0.110908365  0.206298440  0.14269613  0.041439288  0.200221472
## RPL_EBM_DOM2    0.127452928  0.223847971  0.16904291  0.032612698  0.220206609
## EPL_PARK       -0.178276677 -0.126106496 -0.13406281 -0.067780865 -0.142212961
## EPL_HOUAGE     -0.201077156 -0.270817768 -0.21988809 -0.073034636 -0.167462954
## EPL_WLKIND      0.119595305  0.095792529  0.09536510  0.128308888  0.068226603
## SPL_EBM_THEME3 -0.098110592 -0.160474043 -0.12272107  0.010151329 -0.098319500
## RPL_EBM_DOM3   -0.079356606 -0.143165814 -0.12169345  0.022783567 -0.088902970
## EPL_RAIL        0.245553961  0.240083811  0.21567111  0.149539032  0.318756673
## EPL_ROAD        0.043214166  0.015255261  0.07532014  0.001623777  0.073781226
## EPL_AIRPRT      0.052000861  0.060805851  0.01816487  0.041302017  0.003309397
## SPL_EBM_THEME4  0.244476051  0.235178001  0.21323183  0.145618396  0.291193863
## RPL_EBM_DOM4    0.246800228  0.231240594  0.21436155  0.149535452  0.297564798
## EPL_IMPWTR      0.603605225  0.528188603  0.50193822  0.255942547  0.483602366
## SPL_EBM_THEME5  0.603605225  0.528188603  0.50193822  0.255942547  0.483602366
## RPL_EBM_DOM5    0.603551054  0.528168626  0.50189420  0.255858372  0.483671111
## SPL_EBM         0.197019637  0.219969874  0.17941573  0.115067258  0.253801984
## RPL_EBM         0.237896620  0.247593993  0.22181227  0.118962964  0.286299757
## EPL_MINRTY      0.995594477  0.622923193  0.59011516  0.346038596  0.511884310
## SPL_SVM_DOM1    0.995594477  0.622923193  0.59011516  0.346038596  0.511884310
## RPL_SVM_DOM1    0.995594477  0.622923193  0.59011516  0.346038596  0.511884310
## EPL_POV200      0.699389906  0.962636535  0.81515776  0.485332626  0.855339974
## EPL_NOHSDP      0.671810519  0.789297703  0.89010765  0.353634146  0.705953703
## EPL_UNEMP       0.355215732  0.459654871  0.39329701  0.815656456  0.400236391
## EPL_RENTER      0.447194644  0.737541725  0.62691282  0.277468791  0.952920983
## EPL_HOUBDN      0.693796342  0.749919877  0.63964664  0.423839650  0.707977905
## EPL_UNINSUR     0.365336649  0.406081568  0.39796690  0.218873305  0.455959351
## EPL_NOINT       0.466658065  0.565357796  0.56208953  0.238810979  0.536337823
## SPL_SVM_DOM2    0.681938934  0.865320329  0.79451210  0.542080680  0.846785901
## RPL_SVM_DOM2    0.694718891  0.845418118  0.76958656  0.506707478  0.838897054
## EPL_AGE65      -0.587461715 -0.627577679 -0.53200046 -0.353566889 -0.654070040
## EPL_AGE17       0.560806123  0.725615033  0.63489715  0.351648183  0.618614027
## EPL_DISABL      0.029878577  0.173197283  0.19102235  0.152716853  0.091150194
## EPL_LIMENG      0.474211394  0.611611713  0.63059391  0.246581333  0.639920566
## SPL_SVM_DOM3    0.173917982  0.398251434  0.41622828  0.179911005  0.260907415
## RPL_SVM_DOM3    0.181396786  0.407556903  0.41359856  0.181749673  0.281777234
## EPL_MOBILE     -0.029269078 -0.043131435 -0.03006588 -0.046898538 -0.047905474
## EPL_GROUPQ     -0.017224233  0.139053511  0.12050549  0.185275699  0.101072539
## SPL_SVM_DOM4   -0.029087073  0.098974784  0.08932785  0.137013450  0.063892308
## RPL_SVM_DOM4   -0.045112345  0.091404717  0.08542296  0.142291351  0.053082257
## SPL_SVM         0.646267340  0.849218095  0.79437827  0.530441183  0.778933773
## RPL_SVM         0.671493670  0.840684271  0.77961141  0.503555508  0.788161276
## F_BPHIGH        0.283721500  0.137059784  0.15309647  0.102892018  0.009928528
## F_ASTHMA        0.693464970  0.606038074  0.53787372  0.281216646  0.566734807
## F_CANCER       -0.670695133 -0.474425421 -0.45135385 -0.264346404 -0.430514803
## F_MHLTH         0.495137885  0.758301875  0.73109764  0.427835848  0.699318372
## F_DIABETES      0.740003586  0.589401264  0.55926620  0.287701378  0.524497204
## F_HVM           0.616581177  0.638886829  0.60913202  0.338581314  0.538332035
## RPL_HVM         0.616581177  0.638886829  0.60913202  0.338581314  0.538332035
## E_OZONE        -0.290945153 -0.516850942 -0.47652741 -0.264131973 -0.600397803
## E_PM            0.135365945  0.124334352  0.11171290  0.132969447  0.273798669
## E_DSLPM         0.429323448  0.553668597  0.53820635  0.245409162  0.577471189
## E_TOTCR         0.456302190  0.611149172  0.56436769  0.272112537  0.575049960
## E_NPL                    NA           NA          NA           NA           NA
## E_TRI           0.218911982  0.230228651  0.23895994  0.020956590  0.148549515
## E_TSD           0.001753528  0.009679261 -0.03791915  0.008259653  0.028542440
## E_RMP          -0.041209450  0.025828865 -0.03338917 -0.027625828  0.152099146
## E_COAL                   NA           NA          NA           NA           NA
## E_LEAD                   NA           NA          NA           NA           NA
## E_PARK          0.174900225  0.124065167  0.13277840  0.066557412  0.139101194
## E_HOUAGE       -0.197085830 -0.262985508 -0.20757229 -0.064144904 -0.161010609
## E_WLKIND       -0.122829270 -0.102494187 -0.09681975 -0.131654148 -0.073024918
## E_RAIL          0.243811335  0.240156672  0.21702568  0.160411787  0.327602795
## E_ROAD          0.025612689 -0.001654406  0.06378699 -0.012198977  0.062045134
## E_AIRPRT        0.032602139  0.059297937  0.04880384  0.009804192  0.032920399
## E_IMPWTR        0.566679919  0.469375096  0.45027183  0.246109465  0.423676663
## EP_MINRTY       1.000000000  0.622085632  0.58815215  0.337975636  0.515741585
## EP_POV200       0.622085632  1.000000000  0.83685287  0.509812541  0.832681029
## EP_NOHSDP       0.588152153  0.836852872  1.00000000  0.410259219  0.719133692
## EP_UNEMP        0.337975636  0.509812541  0.41025922  1.000000000  0.366292284
## EP_RENTER       0.515741585  0.832681029  0.71913369  0.366292284  1.000000000
## EP_HOUBDN       0.581458454  0.790594313  0.63766735  0.504472595  0.685620205
## EP_UNINSUR      0.329459281  0.390526504  0.38218079  0.205975113  0.434073198
## EP_NOINT        0.433352243  0.557117887  0.56557149  0.214426539  0.511024331
## EP_AGE65       -0.593289077 -0.560591847 -0.49839048 -0.290855292 -0.601155320
## EP_AGE17        0.527549320  0.674249337  0.60444972  0.280190603  0.568509770
## EP_DISABL      -0.039213762  0.208863432  0.14082108  0.239441903  0.075144459
## EP_LIMENG       0.442701988  0.625279035  0.65837782  0.246951368  0.674528583
## EP_MOBILE      -0.044307759 -0.090205065 -0.06351061 -0.077972558 -0.093511493
## EP_GROUPQ      -0.275186510  0.013493651 -0.08396543  0.124535278 -0.059750400
## EP_BPHIGH       0.335166391  0.201301233  0.19237009  0.118565006  0.020432651
## EP_ASTHMA       0.650352420  0.690197977  0.65162902  0.393695141  0.514720440
## EP_CANCER      -0.708854632 -0.646563833 -0.57517976 -0.384888851 -0.645130840
## EP_MHLTH        0.622777948  0.904031263  0.85086180  0.484325597  0.778273949
## EP_DIABETES     0.627310667  0.755489723  0.70934240  0.325431918  0.555682374
## EPL_BPHIGH      0.377817502  0.228223093  0.23468259  0.136588044  0.052375316
## EPL_ASTHMA      0.773573053  0.698843216  0.66289322  0.362276417  0.582520321
## EPL_CANCER     -0.759139564 -0.664509597 -0.60155522 -0.394789591 -0.655729134
## EPL_DIABETES    0.795432987  0.719176733  0.69024580  0.341321926  0.573364536
## EPL_MHLTH       0.664455175  0.909615572  0.85160069  0.490498089  0.818879607
##                   EP_HOUBDN   EP_UNINSUR     EP_NOINT     EP_AGE65
## E_TOTPOP        0.049183523  0.178761415  0.090422389 -0.160133244
## M_TOTPOP        0.089727934  0.226720802  0.121999506 -0.195020522
## E_DAYPOP        0.039455670  0.066084694  0.043346061  0.006000718
## SPL_EJI         0.639389119  0.387141230  0.625370322 -0.421463367
## RPL_EJI         0.639001419  0.397788252  0.578503713 -0.412061868
## SPL_SER         0.701270446  0.490432859  0.542340487 -0.496968905
## RPL_SER         0.687581320  0.466539989  0.512276256 -0.478725003
## EPL_OZONE      -0.333309272 -0.258590328 -0.317991048  0.294970916
## EPL_PM          0.197937527  0.182253308  0.048810163 -0.111483773
## EPL_DSLPM       0.471330780  0.277092541  0.338068309 -0.414123355
## EPL_TOTCR       0.466621003  0.268981625  0.354365922 -0.399034195
## SPL_EBM_THEME1  0.215942477  0.063182946  0.034703911 -0.153100684
## RPL_EBM_DOM1    0.201161486  0.050521786  0.029634659 -0.137967570
## EPL_NPL                  NA           NA           NA           NA
## EPL_TRI         0.069158787  0.058407643  0.203403721 -0.076331840
## EPL_TSD        -0.007854507  0.093086188 -0.040044952 -0.087748064
## EPL_RMP         0.074778915  0.041250770 -0.148683350 -0.053899001
## EPL_COAL                 NA           NA           NA           NA
## EPL_LEAD                 NA           NA           NA           NA
## SPL_EBM_THEME2  0.128194901  0.103455870  0.065087803 -0.130575343
## RPL_EBM_DOM2    0.134755502  0.099685162  0.073324698 -0.132023427
## EPL_PARK       -0.098877679 -0.050027769 -0.073512125  0.063811507
## EPL_HOUAGE     -0.142754999 -0.063239004 -0.265890125  0.221436113
## EPL_WLKIND      0.045879139  0.004066295  0.135831773  0.049173892
## SPL_EBM_THEME3 -0.089087788 -0.048655470 -0.131820188  0.197855550
## RPL_EBM_DOM3   -0.078325270 -0.049572536 -0.130056288  0.187357397
## EPL_RAIL        0.291705328  0.224733153  0.161287424 -0.107242703
## EPL_ROAD        0.037475081  0.019948928 -0.003932019 -0.044907479
## EPL_AIRPRT      0.022602497  0.025230767  0.061010197  0.023845562
## SPL_EBM_THEME4  0.266415927  0.206227649  0.163394217 -0.092106544
## RPL_EBM_DOM4    0.273790985  0.215562806  0.157735648 -0.092902584
## EPL_IMPWTR      0.505527053  0.357324485  0.266850911 -0.528172451
## SPL_EBM_THEME5  0.505527053  0.357324485  0.266850911 -0.528172451
## RPL_EBM_DOM5    0.505577575  0.357338618  0.266825739 -0.528167242
## SPL_EBM         0.207430976  0.161244776  0.070604669 -0.100740715
## RPL_EBM         0.230590189  0.174935622  0.092370725 -0.124100681
## EPL_MINRTY      0.580522652  0.317269945  0.433111048 -0.590787541
## SPL_SVM_DOM1    0.580522652  0.317269945  0.433111048 -0.590787541
## RPL_SVM_DOM1    0.580522652  0.317269945  0.433111048 -0.590787541
## EPL_POV200      0.802502243  0.446655227  0.555505642 -0.632198976
## EPL_NOHSDP      0.654247660  0.426184178  0.514806814 -0.578548447
## EPL_UNEMP       0.445624758  0.330618747  0.203427579 -0.345450769
## EPL_RENTER      0.599710394  0.413978173  0.494332557 -0.566020766
## EPL_HOUBDN      0.862606352  0.429272365  0.423174703 -0.626481160
## EPL_UNINSUR     0.402314805  0.968455679  0.188399432 -0.469799189
## EPL_NOINT       0.375112786  0.220390794  0.960078452 -0.379850241
## SPL_SVM_DOM2    0.762690587  0.614142302  0.616613320 -0.663611832
## RPL_SVM_DOM2    0.762776448  0.580845724  0.589726713 -0.662481501
## EPL_AGE65      -0.567489242 -0.475720654 -0.295302858  0.939372902
## EPL_AGE17       0.557226689  0.334798214  0.375961799 -0.654215416
## EPL_DISABL      0.029323506 -0.126125233  0.325399859  0.138541074
## EPL_LIMENG      0.535687844  0.384148775  0.341412633 -0.467399617
## SPL_SVM_DOM3    0.206353350 -0.035611961  0.372558692  0.110873828
## RPL_SVM_DOM3    0.241858532  0.023305042  0.333245274  0.061580292
## EPL_MOBILE     -0.048412730  0.002453157 -0.002906652 -0.002757004
## EPL_GROUPQ      0.101979641  0.084131027  0.091745748  0.044302306
## SPL_SVM_DOM4    0.064428138  0.073762037  0.077724509  0.036873706
## RPL_SVM_DOM4    0.060415822  0.050702065  0.059762992  0.060815807
## SPL_SVM         0.706304441  0.507848804  0.629885792 -0.518689581
## RPL_SVM         0.728806918  0.503636045  0.601700897 -0.533890888
## F_BPHIGH       -0.013136033 -0.180993953  0.304196495  0.156648963
## F_ASTHMA        0.555669677  0.389220164  0.410442242 -0.518738602
## F_CANCER       -0.471704680 -0.280318677 -0.328978324  0.657504355
## F_MHLTH         0.561064145  0.355622993  0.592429011 -0.523198605
## F_DIABETES      0.510621772  0.283917168  0.438904588 -0.360060555
## F_HVM           0.452022689  0.217079610  0.565581324 -0.268099480
## RPL_HVM         0.452022689  0.217079610  0.565581324 -0.268099480
## E_OZONE        -0.393716434 -0.303416318 -0.320083972  0.336395539
## E_PM            0.203297393  0.189278988  0.056686675 -0.117254222
## E_DSLPM         0.463448943  0.286165871  0.335302884 -0.416027133
## E_TOTCR         0.466289861  0.287414223  0.375688335 -0.406619884
## E_NPL                    NA           NA           NA           NA
## E_TRI           0.094195894  0.102280627  0.222311956 -0.118070996
## E_TSD          -0.007854507  0.093086188 -0.040044952 -0.087748064
## E_RMP           0.062734056  0.053447852 -0.140078502 -0.053262827
## E_COAL                   NA           NA           NA           NA
## E_LEAD                   NA           NA           NA           NA
## E_PARK          0.097551511  0.046437992  0.070289565 -0.065564646
## E_HOUAGE       -0.136289318 -0.058283821 -0.253295521  0.218916248
## E_WLKIND       -0.047480554 -0.009735466 -0.132864227 -0.049409858
## E_RAIL          0.295377215  0.224737735  0.149363779 -0.110413477
## E_ROAD          0.023606821  0.021055540 -0.012870416 -0.041389092
## E_AIRPRT        0.039677496  0.053033483  0.066921450 -0.035967571
## E_IMPWTR        0.464850505  0.319689599  0.246818142 -0.483471893
## EP_MINRTY       0.581458454  0.329459281  0.433352243 -0.593289077
## EP_POV200       0.790594313  0.390526504  0.557117887 -0.560591847
## EP_NOHSDP       0.637667347  0.382180794  0.565571486 -0.498390481
## EP_UNEMP        0.504472595  0.205975113  0.214426539 -0.290855292
## EP_RENTER       0.685620205  0.434073198  0.511024331 -0.601155320
## EP_HOUBDN       1.000000000  0.377860348  0.353561781 -0.490761586
## EP_UNINSUR      0.377860348  1.000000000  0.182950221 -0.454156169
## EP_NOINT        0.353561781  0.182950221  1.000000000 -0.308984482
## EP_AGE65       -0.490761586 -0.454156169 -0.308984482  1.000000000
## EP_AGE17        0.483200269  0.272362161  0.384615455 -0.645012454
## EP_DISABL       0.158785768 -0.115711403  0.160509508  0.273840000
## EP_LIMENG       0.568340965  0.472811800  0.319817722 -0.466240002
## EP_MOBILE      -0.095821107 -0.017295516 -0.014783973  0.027104254
## EP_GROUPQ       0.085520796 -0.138129783 -0.163981916  0.333607198
## EP_BPHIGH       0.053209499 -0.074640191  0.316236246  0.232955332
## EP_ASTHMA       0.540280019  0.192419998  0.600822541 -0.451441150
## EP_CANCER      -0.651810068 -0.449092161 -0.335682285  0.855705989
## EP_MHLTH        0.730607637  0.378433031  0.632819445 -0.644290625
## EP_DIABETES     0.542327534  0.184952948  0.614625275 -0.251075878
## EPL_BPHIGH      0.068323322 -0.057386233  0.351851643  0.177642218
## EPL_ASTHMA      0.586892277  0.361777508  0.543439212 -0.581839120
## EPL_CANCER     -0.659821331 -0.443165741 -0.382530207  0.822363244
## EPL_DIABETES    0.544263360  0.326928739  0.531061650 -0.353042416
## EPL_MHLTH       0.738927940  0.444217078  0.626157676 -0.678427601
##                     EP_AGE17     EP_DISABL    EP_LIMENG     EP_MOBILE
## E_TOTPOP        0.1828314472 -0.0606119005  0.173441610 -0.0812259110
## M_TOTPOP        0.1957589634 -0.0706051676  0.159041731 -0.0602584160
## E_DAYPOP       -0.0711693707  0.0889629683  0.001210396  0.0080282637
## SPL_EJI         0.5238353632  0.1814879602  0.512676896 -0.0449196760
## RPL_EJI         0.4959133064  0.1265223766  0.500632794 -0.0510024916
## SPL_SER         0.5304188066  0.1502062569  0.623337768  0.0158246839
## RPL_SER         0.4929988654  0.1221400939  0.584887716  0.0076454931
## EPL_OZONE      -0.3388139400 -0.0588487253 -0.503035148  0.0661825118
## EPL_PM          0.0691672523 -0.1833049001  0.258820646  0.0699303256
## EPL_DSLPM       0.3918029967  0.0445013654  0.591527463 -0.1045551434
## EPL_TOTCR       0.3886084677  0.1203041165  0.496953756 -0.1054677644
## SPL_EBM_THEME1  0.0628862724 -0.0169899389  0.076484393 -0.0177847457
## RPL_EBM_DOM1    0.0525645906 -0.0278662354  0.063262797 -0.0283702838
## EPL_NPL                   NA            NA           NA            NA
## EPL_TRI         0.1285087372  0.1262139322  0.054913722 -0.0918225481
## EPL_TSD         0.0375029460  0.0025869926 -0.054364746 -0.0177569198
## EPL_RMP        -0.0731207353 -0.1354196067  0.158825284  0.0676536140
## EPL_COAL                  NA            NA           NA            NA
## EPL_LEAD                  NA            NA           NA            NA
## SPL_EBM_THEME2  0.0671654897  0.0078714441  0.178769006 -0.0338174985
## RPL_EBM_DOM2    0.0749208067  0.0061575613  0.215796902 -0.0371718770
## EPL_PARK       -0.0931617848  0.0320558824 -0.102288713 -0.0247455920
## EPL_HOUAGE     -0.2844206813 -0.0106727207 -0.034525574  0.1107001883
## EPL_WLKIND      0.0344459547  0.0977588422  0.012062339 -0.0014088667
## SPL_EBM_THEME3 -0.2019504945  0.0468686926 -0.025854129  0.0813401555
## RPL_EBM_DOM3   -0.1927022334  0.0587228735 -0.023001059  0.0772961153
## EPL_RAIL        0.1142019152 -0.1623750581  0.214869618  0.0410933559
## EPL_ROAD        0.0125814695 -0.0766596544  0.069434554 -0.0085633010
## EPL_AIRPRT     -0.0002123141  0.0003691784  0.018087723  0.0837409606
## SPL_EBM_THEME4  0.0991117458 -0.1600617112  0.210605591  0.0730878969
## RPL_EBM_DOM4    0.1023910201 -0.1663419547  0.214800524  0.0614238595
## EPL_IMPWTR      0.3682332383  0.0173317992  0.466531748 -0.0839527065
## SPL_EBM_THEME5  0.3682332383  0.0173317992  0.466531748 -0.0839527065
## RPL_EBM_DOM5    0.3681773063  0.0173274235  0.466601054 -0.0838585108
## SPL_EBM         0.0317158284 -0.0249607044  0.240161818  0.0258304011
## RPL_EBM         0.0611891612 -0.0516869059  0.267309248  0.0193520201
## EPL_MINRTY      0.5284192254 -0.0251828627  0.441997026 -0.0502430014
## SPL_SVM_DOM1    0.5284192254 -0.0251828627  0.441997026 -0.0502430014
## RPL_SVM_DOM1    0.5284192254 -0.0251828627  0.441997026 -0.0502430014
## EPL_POV200      0.6597568296  0.1412820654  0.657259304 -0.0898807976
## EPL_NOHSDP      0.5789129176  0.0945714600  0.622966778 -0.0367030268
## EPL_UNEMP       0.2716076425  0.1100038919  0.294802811 -0.0633587421
## EPL_RENTER      0.5285400425  0.0375545930  0.579524263 -0.0801928114
## EPL_HOUBDN      0.5019677279  0.0580550697  0.541213094 -0.0922114659
## EPL_UNINSUR     0.2741928716 -0.1063405587  0.476583757 -0.0127607343
## EPL_NOINT       0.4236403327  0.1050605502  0.335051340 -0.0057583965
## SPL_SVM_DOM2    0.5971206744  0.0837558487  0.647082606 -0.0705801878
## RPL_SVM_DOM2    0.5793695431  0.0727844772  0.623732623 -0.0682334492
## EPL_AGE65      -0.6382261731  0.1873327394 -0.504651099  0.0534043563
## EPL_AGE17       0.9544676345 -0.0687956051  0.492988342 -0.0699191118
## EPL_DISABL      0.0066115140  0.8142164411 -0.073997968  0.0106645990
## EPL_LIMENG      0.4866894833 -0.0298011118  0.813643588 -0.1927334064
## SPL_SVM_DOM3    0.4235434252  0.5446192695  0.238731110 -0.0733027202
## RPL_SVM_DOM3    0.4475350609  0.4864873628  0.273291849 -0.1009311602
## EPL_MOBILE     -0.0421914527 -0.0232520273 -0.012481537  0.8829359823
## EPL_GROUPQ      0.0165497876  0.1095498645  0.103568588  0.0132007567
## SPL_SVM_DOM4   -0.0062369495  0.0831905111  0.083267542  0.4406472939
## RPL_SVM_DOM4   -0.0165714432  0.0891040002  0.069374070  0.4247668243
## SPL_SVM         0.6135718905  0.2302389565  0.619768972  0.0447907507
## RPL_SVM         0.6013828909  0.2008629065  0.620206932  0.0101808625
## F_BPHIGH        0.0109841839  0.2254307017 -0.215586770  0.0106027645
## F_ASTHMA        0.4147315073  0.0410199266  0.366289333 -0.0473696036
## F_CANCER       -0.4099132016  0.0561308363 -0.330607818 -0.0664175312
## F_MHLTH         0.5703924493  0.0948883507  0.571819840 -0.0769637196
## F_DIABETES      0.4192993461  0.0286742532  0.390887280 -0.0859193857
## F_HVM           0.4082729994  0.1703170134  0.309939851 -0.0877410580
## RPL_HVM         0.4082729994  0.1703170134  0.309939851 -0.0877410580
## E_OZONE        -0.3590823987 -0.0275696617 -0.557231113  0.0535782824
## E_PM            0.0735567868 -0.1811825888  0.261221989  0.0682438976
## E_DSLPM         0.3925155397  0.0511828458  0.625276414 -0.0953785301
## E_TOTCR         0.3999033891  0.1508425500  0.501773188 -0.1051516647
## E_NPL                     NA            NA           NA            NA
## E_TRI           0.1465748630  0.1109443087  0.076570341 -0.1109477139
## E_TSD           0.0375029460  0.0025869926 -0.054364746 -0.0177569198
## E_RMP          -0.0119654092 -0.1422742437  0.213566081  0.0267452130
## E_COAL                    NA            NA           NA            NA
## E_LEAD                    NA            NA           NA            NA
## E_PARK          0.0886699009 -0.0355029459  0.100437363  0.0243602448
## E_HOUAGE       -0.2808127128 -0.0043829617 -0.032847291  0.1109538606
## E_WLKIND       -0.0364069245 -0.0987765550 -0.016153595  0.0039022652
## E_RAIL          0.1140022697 -0.1681147754  0.224590499  0.0297551660
## E_ROAD          0.0046614008 -0.0782413938  0.061444589 -0.0190990365
## E_AIRPRT        0.0139932168 -0.0423404545  0.044295334  0.0033392104
## E_IMPWTR        0.3218020914  0.0315238045  0.375806294 -0.0649976609
## EP_MINRTY       0.5275493195 -0.0392137619  0.442701988 -0.0443077589
## EP_POV200       0.6742493368  0.2088634323  0.625279035 -0.0902050646
## EP_NOHSDP       0.6044497152  0.1408210821  0.658377821 -0.0635106053
## EP_UNEMP        0.2801906027  0.2394419035  0.246951368 -0.0779725583
## EP_RENTER       0.5685097704  0.0751444586  0.674528583 -0.0935114931
## EP_HOUBDN       0.4832002693  0.1587857683  0.568340965 -0.0958211073
## EP_UNINSUR      0.2723621613 -0.1157114029  0.472811800 -0.0172955164
## EP_NOINT        0.3846154554  0.1605095083  0.319817722 -0.0147839729
## EP_AGE65       -0.6450124535  0.2738400003 -0.466240002  0.0271042541
## EP_AGE17        1.0000000000 -0.1663911386  0.449140112 -0.0551118611
## EP_DISABL      -0.1663911386  1.0000000000 -0.107695356 -0.0059359505
## EP_LIMENG       0.4491401118 -0.1076953559  1.000000000 -0.0678058170
## EP_MOBILE      -0.0551118611 -0.0059359505 -0.067805817  1.0000000000
## EP_GROUPQ      -0.3430253985  0.3966217799 -0.154040903  0.0023527312
## EP_BPHIGH       0.0631092290  0.2863474958 -0.152441609 -0.0323865243
## EP_ASTHMA       0.5453755514  0.1061160345  0.225167676 -0.0018987565
## EP_CANCER      -0.5414308247  0.1080095821 -0.551081379  0.0027916260
## EP_MHLTH        0.6810220373  0.0955014640  0.572740971 -0.0560053854
## EP_DIABETES     0.4979448162  0.2295425910  0.387385409 -0.0558673560
## EPL_BPHIGH      0.0989761810  0.2534168419 -0.127837342 -0.0375804254
## EPL_ASTHMA      0.5105388842  0.0836719733  0.357103631 -0.0004207458
## EPL_CANCER     -0.5568551958  0.1015794376 -0.561798974 -0.0032950301
## EPL_DIABETES    0.5208669012  0.1596349935  0.454890833 -0.0906382134
## EPL_MHLTH       0.6724877560  0.1088215395  0.613874037 -0.0550985764
##                    EP_GROUPQ    EP_BPHIGH    EP_ASTHMA    EP_CANCER
## E_TOTPOP       -0.1074750036  0.090970931  0.138921307 -0.144992129
## M_TOTPOP       -0.1175571725  0.120146853  0.185651234 -0.179400052
## E_DAYPOP        0.2951054679 -0.015970754  0.013695233 -0.068758742
## SPL_EJI        -0.0400331281  0.503024027  0.763426251 -0.511763363
## RPL_EJI        -0.0450446444  0.483819345  0.726552279 -0.504149055
## SPL_SER        -0.0510977039  0.163845732  0.539725918 -0.626881685
## RPL_SER        -0.0560700777  0.168318182  0.525440594 -0.606695626
## EPL_OZONE      -0.0009120689 -0.074181122 -0.271320371  0.299252265
## EPL_PM          0.0131926786  0.058537233  0.158729763 -0.128339430
## EPL_DSLPM      -0.0576842727  0.056369495  0.329583370 -0.481525866
## EPL_TOTCR      -0.0132756646  0.071758197  0.333475916 -0.481340262
## SPL_EBM_THEME1 -0.0252957191  0.008750381  0.114799784 -0.252373655
## RPL_EBM_DOM1   -0.0314924813  0.001018599  0.096877803 -0.233497560
## EPL_NPL                   NA           NA           NA           NA
## EPL_TRI        -0.0267760123  0.156466898  0.151576180 -0.108669031
## EPL_TSD         0.0812986482 -0.072784635 -0.040040976 -0.062467155
## EPL_RMP         0.0624343397 -0.326134775 -0.195431172 -0.108306518
## EPL_COAL                  NA           NA           NA           NA
## EPL_LEAD                  NA           NA           NA           NA
## SPL_EBM_THEME2  0.0377957714 -0.133532099 -0.023978069 -0.203903812
## RPL_EBM_DOM2    0.0179592601 -0.122366888 -0.015813661 -0.206628667
## EPL_PARK        0.0724717288 -0.088192505 -0.120552460  0.108154514
## EPL_HOUAGE     -0.0475148332 -0.038972928 -0.236022453  0.220545429
## EPL_WLKIND     -0.0179291513  0.198859948  0.178258311  0.036137279
## SPL_EBM_THEME3 -0.0411396899  0.072842072 -0.089174274  0.192854436
## RPL_EBM_DOM3   -0.0385948622  0.084283381 -0.081311006  0.178849666
## EPL_RAIL       -0.0005683839  0.147016802  0.237582285 -0.187450888
## EPL_ROAD        0.0151211265 -0.005846969  0.044067110 -0.046742023
## EPL_AIRPRT      0.0169751492 -0.019358331  0.003953593 -0.058365324
## SPL_EBM_THEME4  0.0129047392  0.110904273  0.214213706 -0.200402409
## RPL_EBM_DOM4    0.0066379751  0.116794798  0.217379961 -0.196688790
## EPL_IMPWTR     -0.1384693183  0.032383417  0.357064552 -0.624860386
## SPL_EBM_THEME5 -0.1384693183  0.032383417  0.357064552 -0.624860386
## RPL_EBM_DOM5   -0.1384460612  0.032343895  0.357028512 -0.624862314
## SPL_EBM        -0.0016677168 -0.026078824  0.055526193 -0.209699184
## RPL_EBM        -0.0186866442  0.004356150  0.096253707 -0.229591960
## EPL_MINRTY     -0.2612818823  0.333833539  0.651027883 -0.703562622
## SPL_SVM_DOM1   -0.2612818823  0.333833539  0.651027883 -0.703562622
## RPL_SVM_DOM1   -0.2612818823  0.333833539  0.651027883 -0.703562622
## EPL_POV200     -0.0572306985  0.139594370  0.647297791 -0.729754810
## EPL_NOHSDP     -0.0808544188  0.169073375  0.612624578 -0.644241120
## EPL_UNEMP       0.0423202704  0.088806867  0.341807397 -0.418045311
## EPL_RENTER     -0.0986419896  0.010755227  0.453872896 -0.574067220
## EPL_HOUBDN     -0.1045455280  0.053308536  0.544902077 -0.736945509
## EPL_UNINSUR    -0.1561214206 -0.046125756  0.222088927 -0.473022455
## EPL_NOINT      -0.1918389938  0.279097669  0.597730591 -0.399867940
## SPL_SVM_DOM2   -0.1171181192  0.130973624  0.631837055 -0.734557967
## RPL_SVM_DOM2   -0.1245411252  0.130536116  0.626504072 -0.738151970
## EPL_AGE65       0.1659103299  0.181721223 -0.458382794  0.820069046
## EPL_AGE17      -0.2353434536  0.043825068  0.518905754 -0.604051891
## EPL_DISABL      0.0343245252  0.272947579  0.152228816  0.097991449
## EPL_LIMENG     -0.1566261053 -0.124388422  0.214571425 -0.513998319
## SPL_SVM_DOM3   -0.0899411169  0.280079929  0.218292851  0.022681463
## RPL_SVM_DOM3   -0.0768505590  0.252877925  0.217301949 -0.000246486
## EPL_MOBILE     -0.0238899289 -0.036698905  0.008428629 -0.026708583
## EPL_GROUPQ      0.4137544493  0.017130351  0.033586361 -0.011265996
## SPL_SVM_DOM4    0.3452798473 -0.003065835  0.033068559 -0.022702796
## RPL_SVM_DOM4    0.3903151001  0.001416840  0.024937643 -0.004560913
## SPL_SVM        -0.0402050926  0.203123779  0.606990644 -0.622858661
## RPL_SVM        -0.0522695124  0.192207242  0.596883525 -0.641107794
## F_BPHIGH        0.0335131393  0.789102666  0.528435094  0.159279150
## F_ASTHMA       -0.1366892872  0.333352018  0.651914281 -0.586257668
## F_CANCER        0.2503823200  0.054402192 -0.453387675  0.746400602
## F_MHLTH        -0.0587586379  0.180349173  0.662576571 -0.559027121
## F_DIABETES     -0.0977804981  0.505785607  0.632864329 -0.435212280
## F_HVM          -0.0221177209  0.689213268  0.795662249 -0.305384177
## RPL_HVM        -0.0221177209  0.689213268  0.795662249 -0.305384177
## E_OZONE         0.0006549523 -0.010941309 -0.255663904  0.368422565
## E_PM            0.0138148580  0.066549469  0.169701192 -0.136015369
## E_DSLPM        -0.0701781240  0.067099159  0.334944469 -0.460212575
## E_TOTCR        -0.0115963574  0.098169139  0.357270970 -0.475770473
## E_NPL                     NA           NA           NA           NA
## E_TRI          -0.0258052236  0.140038830  0.147105825 -0.157067461
## E_TSD           0.0812986482 -0.072784635 -0.040040976 -0.062467155
## E_RMP          -0.0414343787 -0.250923924 -0.176451154 -0.082100267
## E_COAL                    NA           NA           NA           NA
## E_LEAD                    NA           NA           NA           NA
## E_PARK         -0.0624271391  0.081805948  0.119067213 -0.111592327
## E_HOUAGE       -0.0419309018 -0.034089585 -0.227030924  0.217404733
## E_WLKIND        0.0170798704 -0.205236587 -0.183150746 -0.040596142
## E_RAIL          0.0082184800  0.145192849  0.236839403 -0.186202155
## E_ROAD          0.0133797700 -0.009674720  0.034635043 -0.030550952
## E_AIRPRT        0.0593832904 -0.027268319  0.012102655 -0.065874381
## E_IMPWTR       -0.1259261286  0.048332756  0.355022169 -0.581766213
## EP_MINRTY      -0.2751865102  0.335166391  0.650352420 -0.708854632
## EP_POV200       0.0134936506  0.201301233  0.690197977 -0.646563833
## EP_NOHSDP      -0.0839654289  0.192370090  0.651629022 -0.575179755
## EP_UNEMP        0.1245352784  0.118565006  0.393695141 -0.384888851
## EP_RENTER      -0.0597504000  0.020432651  0.514720440 -0.645130840
## EP_HOUBDN       0.0855207963  0.053209499  0.540280019 -0.651810068
## EP_UNINSUR     -0.1381297827 -0.074640191  0.192419998 -0.449092161
## EP_NOINT       -0.1639819156  0.316236246  0.600822541 -0.335682285
## EP_AGE65        0.3336071981  0.232955332 -0.451441150  0.855705989
## EP_AGE17       -0.3430253985  0.063109229  0.545375551 -0.541430825
## EP_DISABL       0.3966217799  0.286347496  0.106116035  0.108009582
## EP_LIMENG      -0.1540409029 -0.152441609  0.225167676 -0.551081379
## EP_MOBILE       0.0023527312 -0.032386524 -0.001898757  0.002791626
## EP_GROUPQ       1.0000000000 -0.010057283 -0.091329443  0.152250140
## EP_BPHIGH      -0.0100572829  1.000000000  0.577337965  0.258749355
## EP_ASTHMA      -0.0913294426  0.577337965  1.000000000 -0.464572883
## EP_CANCER       0.1522501403  0.258749355 -0.464572883  1.000000000
## EP_MHLTH       -0.0631949783  0.214263911  0.842879638 -0.688146487
## EP_DIABETES    -0.0977089683  0.683916765  0.820013704 -0.280260311
## EPL_BPHIGH     -0.0266234374  0.976243178  0.622455608  0.194253113
## EPL_ASTHMA     -0.1180738087  0.469565733  0.872346264 -0.639614143
## EPL_CANCER      0.1619180165  0.184458754 -0.489951624  0.965149622
## EPL_DIABETES   -0.1725101724  0.651814786  0.735848372 -0.405579470
## EPL_MHLTH      -0.0626184546  0.195370418  0.790418165 -0.743933368
##                     EP_MHLTH  EP_DIABETES   EPL_BPHIGH    EPL_ASTHMA
## E_TOTPOP        0.1440892774  0.131260675  0.084142056  0.2002861280
## M_TOTPOP        0.1770018499  0.159736786  0.115766854  0.2598541106
## E_DAYPOP        0.0586769001  0.024572290 -0.020776721  0.0588611062
## SPL_EJI         0.7996123816  0.802809887  0.553117083  0.8315394211
## RPL_EJI         0.7530463670  0.758125195  0.532787761  0.8264365683
## SPL_SER         0.7360947086  0.609860963  0.198726270  0.6604015411
## RPL_SER         0.6974776998  0.581791705  0.201418578  0.6567761702
## EPL_OZONE      -0.4388848281 -0.354692458 -0.097868406 -0.2741081652
## EPL_PM          0.1091238862  0.036819009  0.061954722  0.1619784888
## EPL_DSLPM       0.5399321828  0.442053955  0.080803486  0.4082275300
## EPL_TOTCR       0.5450754431  0.470428651  0.097391233  0.4195363015
## SPL_EBM_THEME1  0.1382188594  0.123235831  0.010304047  0.2177790466
## RPL_EBM_DOM1    0.1205034941  0.105066503  0.003616770  0.1972453394
## EPL_NPL                   NA           NA           NA            NA
## EPL_TRI         0.2180335153  0.279482035  0.185611430  0.1499738207
## EPL_TSD        -0.0006942556 -0.044684238 -0.086003430 -0.0180318128
## EPL_RMP        -0.0690704509 -0.208489024 -0.348862864 -0.1160224462
## EPL_COAL                  NA           NA           NA            NA
## EPL_LEAD                  NA           NA           NA            NA
## SPL_EBM_THEME2  0.1513819708  0.087318000 -0.126421723  0.0441849709
## RPL_EBM_DOM2    0.1651505320  0.113043802 -0.112854794  0.0545006932
## EPL_PARK       -0.1114010346 -0.138833019 -0.095711980 -0.1581355925
## EPL_HOUAGE     -0.2793621148 -0.219821892 -0.064354407 -0.2116731726
## EPL_WLKIND      0.1028982691  0.206347754  0.186104263  0.1176467572
## SPL_EBM_THEME3 -0.1621732238 -0.062846585  0.046294334 -0.1059292708
## RPL_EBM_DOM3   -0.1557283267 -0.053610275  0.053700478 -0.0940948579
## EPL_RAIL        0.2215591860  0.210288717  0.165095788  0.2737632750
## EPL_ROAD        0.0417640101  0.019643596  0.005512190  0.0732419209
## EPL_AIRPRT      0.0434666764  0.028041631 -0.014129834  0.0181652837
## SPL_EBM_THEME4  0.2197736125  0.195496359  0.132268438  0.2609356239
## RPL_EBM_DOM4    0.2162824386  0.196072548  0.139145500  0.2643480209
## EPL_IMPWTR      0.5043048505  0.374117671  0.066083891  0.5209385688
## SPL_EBM_THEME5  0.5043048505  0.374117671  0.066083891  0.5209385688
## RPL_EBM_DOM5    0.5042753982  0.374051715  0.066053752  0.5209555300
## SPL_EBM         0.1702483863  0.145850895 -0.022415989  0.1376009822
## RPL_EBM         0.2019323453  0.186601223  0.014867519  0.1813343200
## EPL_MINRTY      0.6253997847  0.627575221  0.378010365  0.7658348310
## SPL_SVM_DOM1    0.6253997847  0.627575221  0.378010365  0.7658348310
## RPL_SVM_DOM1    0.6253997847  0.627575221  0.378010365  0.7658348310
## EPL_POV200      0.8702791160  0.690631377  0.175148355  0.7363893384
## EPL_NOHSDP      0.7895720108  0.640517316  0.208937173  0.7301608299
## EPL_UNEMP       0.4430654826  0.290916631  0.109919955  0.3897649849
## EPL_RENTER      0.6890262816  0.486065728  0.038189355  0.5416690744
## EPL_HOUBDN      0.7109944634  0.506674390  0.090262917  0.6941173447
## EPL_UNINSUR     0.3904657389  0.203732536 -0.027962311  0.4056460932
## EPL_NOINT       0.6387604282  0.571126596  0.316224058  0.5849942227
## SPL_SVM_DOM2    0.8373212344  0.625458254  0.170621341  0.7527020196
## RPL_SVM_DOM2    0.8157049096  0.612565720  0.168052005  0.7624194878
## EPL_AGE65      -0.6685355514 -0.288292716  0.138775189 -0.5739665027
## EPL_AGE17       0.6914738444  0.488434639  0.075881806  0.5417651917
## EPL_DISABL      0.1362231866  0.250845085  0.272477293  0.1119228875
## EPL_LIMENG      0.5428927985  0.395586067 -0.089121903  0.3214564985
## SPL_SVM_DOM3    0.2981064809  0.437492693  0.284749840  0.1647525766
## RPL_SVM_DOM3    0.3086577924  0.419857843  0.251995134  0.1673244276
## EPL_MOBILE     -0.0229302956 -0.040634871 -0.044941134  0.0141875148
## EPL_GROUPQ      0.1090370357  0.040339341  0.040202084  0.0120765712
## SPL_SVM_DOM4    0.0829045752  0.015040109  0.012828122  0.0173145590
## RPL_SVM_DOM4    0.0730705826  0.008525962  0.015261829  0.0027869666
## SPL_SVM         0.7968560882  0.653536204  0.242940903  0.6906777593
## RPL_SVM         0.7827593274  0.639977352  0.228881622  0.7021937284
## F_BPHIGH        0.1978946402  0.535322627  0.819299560  0.3994579765
## F_ASTHMA        0.6388935921  0.568001434  0.376510839  0.8496561157
## F_CANCER       -0.5282930775 -0.325718475  0.012638661 -0.5771807060
## F_MHLTH         0.8235864884  0.617159626  0.238083707  0.6458102768
## F_DIABETES      0.5838711372  0.676220234  0.544935210  0.7544776409
## F_HVM           0.6864854397  0.800334337  0.741880962  0.8042770394
## RPL_HVM         0.6864854397  0.800334337  0.741880962  0.8042770394
## E_OZONE        -0.4582178912 -0.329361765 -0.038858606 -0.2840245921
## E_PM            0.1190587576  0.045738146  0.071466719  0.1743674630
## E_DSLPM         0.5365504689  0.431828184  0.094373289  0.3994156479
## E_TOTCR         0.5634668388  0.492449837  0.124736144  0.4307478578
## E_NPL                     NA           NA           NA            NA
## E_TRI           0.2291936061  0.277342878  0.171105837  0.1717404667
## E_TSD          -0.0006942556 -0.044684238 -0.086003430 -0.0180318128
## E_RMP          -0.0579122759 -0.148317377 -0.280163993 -0.0944706487
## E_COAL                    NA           NA           NA            NA
## E_LEAD                    NA           NA           NA            NA
## E_PARK          0.1118153204  0.134668041  0.088375857  0.1566922116
## E_HOUAGE       -0.2696121318 -0.212234434 -0.057226132 -0.2027299434
## E_WLKIND       -0.1075181900 -0.214619658 -0.193736174 -0.1214098872
## E_RAIL          0.2223575156  0.205241857  0.162640113  0.2700661126
## E_ROAD          0.0283423378  0.005383470  0.002986434  0.0594617237
## E_AIRPRT        0.0597695373  0.007667649 -0.026457350  0.0288197624
## E_IMPWTR        0.4643366152  0.340619039  0.076458340  0.5137565951
## EP_MINRTY       0.6227779478  0.627310667  0.377817502  0.7735730529
## EP_POV200       0.9040312632  0.755489723  0.228223093  0.6988432160
## EP_NOHSDP       0.8508617971  0.709342396  0.234682588  0.6628932243
## EP_UNEMP        0.4843255973  0.325431918  0.136588044  0.3622764167
## EP_RENTER       0.7782739486  0.555682374  0.052375316  0.5825203208
## EP_HOUBDN       0.7306076368  0.542327534  0.068323322  0.5868922771
## EP_UNINSUR      0.3784330312  0.184952948 -0.057386233  0.3617775079
## EP_NOINT        0.6328194453  0.614625275  0.351851643  0.5434392116
## EP_AGE65       -0.6442906252 -0.251075878  0.177642218 -0.5818391197
## EP_AGE17        0.6810220373  0.497944816  0.098976181  0.5105388842
## EP_DISABL       0.0955014640  0.229542591  0.253416842  0.0836719733
## EP_LIMENG       0.5727409714  0.387385409 -0.127837342  0.3571036313
## EP_MOBILE      -0.0560053854 -0.055867356 -0.037580425 -0.0004207458
## EP_GROUPQ      -0.0631949783 -0.097708968 -0.026623437 -0.1180738087
## EP_BPHIGH       0.2142639108  0.683916765  0.976243178  0.4695657333
## EP_ASTHMA       0.8428796381  0.820013704  0.622455608  0.8723462641
## EP_CANCER      -0.6881464867 -0.280260311  0.194253113 -0.6396141431
## EP_MHLTH        1.0000000000  0.775652225  0.268864418  0.7904896317
## EP_DIABETES     0.7756522245  1.000000000  0.693451554  0.7139582930
## EPL_BPHIGH      0.2688644176  0.693451554  1.000000000  0.5213586789
## EPL_ASTHMA      0.7904896317  0.713958293  0.521358679  1.0000000000
## EPL_CANCER     -0.6938276299 -0.330158236  0.123182926 -0.6533598507
## EPL_DIABETES    0.6979786895  0.874710277  0.681018166  0.8091343282
## EPL_MHLTH       0.9681341996  0.725279743  0.253046530  0.8259283987
##                  EPL_CANCER EPL_DIABETES    EPL_MHLTH
## E_TOTPOP       -0.143152608   0.21414647  0.168604433
## M_TOTPOP       -0.182268395   0.26231020  0.213508039
## E_DAYPOP       -0.041446714   0.02506129  0.067479328
## SPL_EJI        -0.555457278   0.88000177  0.849611389
## RPL_EJI        -0.547689410   0.87036491  0.807295449
## SPL_SER        -0.649638463   0.70902113  0.791070127
## RPL_SER        -0.628415850   0.69054688  0.751169965
## EPL_OZONE       0.346022636  -0.35942418 -0.473858394
## EPL_PM         -0.158106525   0.10887183  0.150326074
## EPL_DSLPM      -0.495368750   0.48284888  0.567114614
## EPL_TOTCR      -0.490764337   0.49251270  0.567845450
## SPL_EBM_THEME1 -0.214421889   0.17655549  0.136835308
## RPL_EBM_DOM1   -0.198109371   0.15976316  0.117036765
## EPL_NPL                  NA           NA           NA
## EPL_TRI        -0.102946278   0.26377191  0.201800660
## EPL_TSD        -0.050348407  -0.03447111  0.008525186
## EPL_RMP        -0.089834324  -0.18029840 -0.045985577
## EPL_COAL                 NA           NA           NA
## EPL_LEAD                 NA           NA           NA
## SPL_EBM_THEME2 -0.181237072   0.09729495  0.156432407
## RPL_EBM_DOM2   -0.185696943   0.12585324  0.168493146
## EPL_PARK        0.127818388  -0.19978320 -0.124698627
## EPL_HOUAGE      0.235221283  -0.18734856 -0.284204020
## EPL_WLKIND      0.010767548   0.16002810  0.065559058
## SPL_EBM_THEME3  0.191410960  -0.06716292 -0.186877204
## RPL_EBM_DOM3    0.176815432  -0.05369894 -0.178147537
## EPL_RAIL       -0.208856459   0.26479914  0.245970998
## EPL_ROAD       -0.065314222   0.04819320  0.053088312
## EPL_AIRPRT     -0.056463046   0.04185933  0.040831163
## SPL_EBM_THEME4 -0.223343298   0.25708384  0.242488645
## RPL_EBM_DOM4   -0.220362948   0.25991180  0.240112578
## EPL_IMPWTR     -0.627877351   0.49872494  0.562673191
## SPL_EBM_THEME5 -0.627877351   0.49872494  0.562673191
## RPL_EBM_DOM5   -0.627882597   0.49869467  0.562672374
## SPL_EBM        -0.198325266   0.18759443  0.175795809
## RPL_EBM        -0.224213981   0.23677726  0.209418399
## EPL_MINRTY     -0.751935026   0.79242664  0.663503459
## SPL_SVM_DOM1   -0.751935026   0.79242664  0.663503459
## RPL_SVM_DOM1   -0.751935026   0.79242664  0.663503459
## EPL_POV200     -0.752684853   0.73677575  0.916779502
## EPL_NOHSDP     -0.677927071   0.72633903  0.827531193
## EPL_UNEMP      -0.423922951   0.37064772  0.490190160
## EPL_RENTER     -0.583170663   0.51907834  0.736308499
## EPL_HOUBDN     -0.745288684   0.60914409  0.757725732
## EPL_UNINSUR    -0.465400069   0.35765933  0.462100276
## EPL_NOINT      -0.449385504   0.53884017  0.652908644
## SPL_SVM_DOM2   -0.756833609   0.71278346  0.896217570
## RPL_SVM_DOM2   -0.759258261   0.71186314  0.876682414
## EPL_AGE65       0.834895999  -0.40582081 -0.719345184
## EPL_AGE17      -0.623898814   0.54707453  0.722444400
## EPL_DISABL      0.071074787   0.20241364  0.147858095
## EPL_LIMENG     -0.537177974   0.47303440  0.574049704
## SPL_SVM_DOM3   -0.004924552   0.39468348  0.301850997
## RPL_SVM_DOM3   -0.021326326   0.40254601  0.316235630
## EPL_MOBILE     -0.031605337  -0.07292779 -0.017140229
## EPL_GROUPQ     -0.008909423   0.06696525  0.131724702
## SPL_SVM_DOM4   -0.023050749   0.02230699  0.105289385
## RPL_SVM_DOM4   -0.004425679   0.01123089  0.092614984
## SPL_SVM        -0.651567603   0.72525739  0.852402843
## RPL_SVM        -0.670453110   0.73525076  0.844583223
## F_BPHIGH        0.093319992   0.45806526  0.176590441
## F_ASTHMA       -0.608793076   0.71412089  0.697578027
## F_CANCER        0.803831213  -0.40513775 -0.565557972
## F_MHLTH        -0.576789846   0.59997202  0.861422527
## F_DIABETES     -0.510378641   0.84772245  0.642907054
## F_HVM          -0.357918936   0.84243681  0.721714566
## RPL_HVM        -0.357918936   0.84243681  0.721714566
## E_OZONE         0.416170774  -0.35793360 -0.513409976
## E_PM           -0.165418689   0.11923932  0.160222484
## E_DSLPM        -0.463042650   0.46274456  0.562542702
## E_TOTCR        -0.483951306   0.50267674  0.586378386
## E_NPL                    NA           NA           NA
## E_TRI          -0.149267601   0.27910599  0.225229181
## E_TSD          -0.050348407  -0.03447111  0.008525186
## E_RMP          -0.070497106  -0.10216180 -0.033777127
## E_COAL                   NA           NA           NA
## E_LEAD                   NA           NA           NA
## E_PARK         -0.132620969   0.19271883  0.125139932
## E_HOUAGE        0.231142187  -0.18013708 -0.273423242
## E_WLKIND       -0.013963943  -0.16746113 -0.069085049
## E_RAIL         -0.206910366   0.25841943  0.246098162
## E_ROAD         -0.046204590   0.03181788  0.038189646
## E_AIRPRT       -0.054624121   0.02526804  0.059351475
## E_IMPWTR       -0.586332749   0.46270633  0.517379222
## EP_MINRTY      -0.759139564   0.79543299  0.664455175
## EP_POV200      -0.664509597   0.71917673  0.909615572
## EP_NOHSDP      -0.601555220   0.69024580  0.851600685
## EP_UNEMP       -0.394789591   0.34132193  0.490498089
## EP_RENTER      -0.655729134   0.57336454  0.818879607
## EP_HOUBDN      -0.659821331   0.54426336  0.738927940
## EP_UNINSUR     -0.443165741   0.32692874  0.444217078
## EP_NOINT       -0.382530207   0.53106165  0.626157676
## EP_AGE65        0.822363244  -0.35304242 -0.678427601
## EP_AGE17       -0.556855196   0.52086690  0.672487756
## EP_DISABL       0.101579438   0.15963499  0.108821539
## EP_LIMENG      -0.561798974   0.45489083  0.613874037
## EP_MOBILE      -0.003295030  -0.09063821 -0.055098576
## EP_GROUPQ       0.161918017  -0.17251017 -0.062618455
## EP_BPHIGH       0.184458754   0.65181479  0.195370418
## EP_ASTHMA      -0.489951624   0.73584837  0.790418165
## EP_CANCER       0.965149622  -0.40557947 -0.743933368
## EP_MHLTH       -0.693827630   0.69797869  0.968134200
## EP_DIABETES    -0.330158236   0.87471028  0.725279743
## EPL_BPHIGH      0.123182926   0.68101817  0.253046530
## EPL_ASTHMA     -0.653359851   0.80913433  0.825928399
## EPL_CANCER      1.000000000  -0.47431933 -0.762823969
## EPL_DIABETES   -0.474319333   1.00000000  0.734006867
## EPL_MHLTH      -0.762823969   0.73400687  1.000000000
#RPL_EJI 
#EP_MINRTY
#EP_POV200 # estimate below 200% Poverty line
#EP_NONHSDP # No high school degree
#EP_RENTER # estimate of renters
#EP_HOUBDN # households that make less than 75,000
#ELP_NOINT # Percentile rank of persons with no internet

#EP_ASTHMA # percentage with asthma
#F_CANCER # flag indicating tracts greater than 0.67 percentile rank with cancer
#EP_DIABETES # percentage of individuals with diabetes 
#F_HVM # total number of tertile flags
#EP_MHLTH # percentage of individuals reporting not good mental health 

eji_complex_bronx = eji_base_bronx[, c("NAME", "COUNTY", "RPL_EJI", "EP_MINRTY", "EP_POV200",  "EP_NOHSDP", "EP_RENTER",  "EP_HOUBDN", "EPL_NOINT", "EP_ASTHMA","F_CANCER",  "EP_DIABETES",  "F_HVM",  "EP_MHLTH")]

# Setting seed 
set.seed(123)

train_sample = sample(seq_len(nrow(eji_complex_bronx)), size = 231)
train = eji_complex_bronx[train_sample, ]
test = eji_complex_bronx[-train_sample, ]

# Training data
# Normalizing the data

z = train[, c(3:14)]
means = apply(z, 2, mean)
sds = apply(z, 2, sd)
nor = scale(z, center = means, scale = sds) 

# How many clusters? 
fviz_nbclust(nor, kmeans, method = "silhouette") # 2 clusters

# K Means on 2 Clusters
kmeans_result = kmeans(nor, centers = 2)  # default gives 48.3%
kmeans_result 
## K-means clustering with 2 clusters of sizes 155, 76
## 
## Cluster means:
##      RPL_EJI  EP_MINRTY  EP_POV200  EP_NOHSDP  EP_RENTER  EP_HOUBDN  EPL_NOINT
## 1  0.5270756  0.4366952  0.5737872  0.5315267  0.5193415  0.4784659  0.4626970
## 2 -1.0749568 -0.8906284 -1.1702239 -1.0840347 -1.0591834 -0.9758187 -0.9436584
##    EP_ASTHMA   F_CANCER EP_DIABETES      F_HVM   EP_MHLTH
## 1  0.4537587 -0.3237398   0.4528685  0.4660311  0.5497016
## 2 -0.9254289  0.6602589  -0.9236133 -0.9504582 -1.1211019
## 
## Clustering vector:
## 42807 42638 42823 42935 42745 42928 42858 42873 42959 42780 42715 42716 42885 
##     1     1     2     2     1     1     2     1     2     1     2     1     1 
## 42825 42949 42764 42650 42631 42944 42883 42839 42703 42706 42667 42770 42656 
##     1     2     1     1     1     1     1     2     1     1     1     1     1 
## 42736 42892 42647 42762 42853 42793 42845 42919 42694 42697 42701 42688 42768 
##     1     1     1     2     2     1     2     1     1     2     1     1     1 
## 42838 42951 42906 42665 42950 42852 42640 42743 42719 42891 42864 42711 42663 
##     2     2     1     1     2     1     1     1     2     1     2     2     1 
## 42786 42869 42837 42658 42627 42637 42925 42872 42714 42649 42907 42748 42737 
##     1     2     2     1     2     1     2     2     1     1     1     1     2 
## 42785 42689 42827 42692 42778 42710 42792 42763 42675 42699 42806 42733 42865 
##     1     2     2     1     2     1     2     1     1     2     2     1     2 
## 42724 42948 42842 42754 42832 42840 42801 42641 42818 42670 42678 42790 42861 
##     1     2     2     2     2     2     1     2     1     1     1     1     2 
## 42895 42912 42704 42648 42740 42843 42734 42930 42849 42835 42890 42781 42729 
##     1     1     1     1     1     2     1     1     2     2     1     1     1 
## 42787 42918 42782 42797 42628 42695 42914 42882 42934 42645 42679 42700 42791 
##     1     2     1     2     1     1     1     1     2     1     1     1     1 
## 42708 42908 42871 42941 42932 42672 42702 42841 42812 42738 42876 42824 42624 
##     1     1     2     1     1     1     2     2     2     1     1     1     2 
## 42795 42654 42867 42848 42713 42939 42804 42644 42731 42718 42879 42676 42735 
##     1     1     2     2     1     2     2     1     1     1     1     2     1 
## 42646 42805 42666 42683 42709 42635 42896 42887 42900 42889 42933 42862 42859 
##     1     1     2     1     1     1     1     1     1     1     1     1     2 
## 42875 42799 42855 42660 42769 42947 42752 42657 42664 42634 42828 42633 42942 
##     1     1     1     1     2     1     1     2     1     2     1     1     1 
## 42854 42685 42779 42922 42958 42954 42943 42794 42742 42888 42677 42784 42822 
##     1     2     1     1     1     2     1     1     1     1     1     1     2 
## 42810 42898 42817 42929 42788 42916 42681 42732 42728 42931 42952 42868 42761 
##     2     1     2     1     1     1     1     1     1     1     2     1     1 
## 42946 42756 42940 42910 42937 42653 42772 42651 42884 42789 42684 42744 42808 
##     2     2     1     2     1     1     2     1     1     1     1     1     2 
## 42917 42811 42629 42741 42826 42655 42819 42874 42893 42661 42915 42821 42659 
##     1     2     1     2     2     1     1     2     1     1     1     1     1 
## 42899 42857 42691 42903 42880 42723 42851 42774 42632 42844 
##     1     1     1     1     1     2     2     1     1     2 
## 
## Within cluster sum of squares by cluster:
## [1] 632.9354 794.6717
##  (between_SS / total_SS =  48.3 %)
## 
## Available components:
## 
## [1] "cluster"      "centers"      "totss"        "withinss"     "tot.withinss"
## [6] "betweenss"    "size"         "iter"         "ifault"
# Plot of Cluster
fviz_cluster(kmeans_result, data = nor)

# Silhouette coefficient
sil = as.data.frame(silhouette(kmeans_result$cluster, dist(nor)))
mean(sil$sil_width) # 0.45 <- worse than simplistic model
## [1] 0.4533216
fviz_silhouette(silhouette(kmeans_result$cluster, dist(nor)))
##   cluster size ave.sil.width
## 1       1  155          0.56
## 2       2   76          0.24

# Adding Clusters to data set
train = train %>% 
  mutate(km.group = factor(kmeans_result$cluster, labels=c("cl1","cl2"))) 

# Summarizing the cluster groups
train %>%
  group_by(km.group) %>%
  summarise(count = n(),
            RPL_EJI = mean(RPL_EJI),
            EP_MINRTY = mean(EP_MINRTY),
            EP_POV200 = mean(EP_POV200),
            EP_NOHSDP = mean(EP_NOHSDP),
            EP_RENTER = mean(EP_RENTER),
            EP_HOUBDN = mean(EP_HOUBDN),
            EPL_NOINT = mean(EPL_NOINT),
            EP_ASTHMA = mean(EP_ASTHMA),
            F_CANCER = mean(F_CANCER),
            EP_DIABETES = mean(EP_DIABETES),
            F_HVM = mean(F_HVM),
            EP_MHLTH = mean(EP_MHLTH))
# 67% are in cluster 1 (higher ratings) <- minorities
# 33% are in cluster 2 (lower ratings) <- non-minorities

# higher across the board for everything except for the flag for cancer 

Testing Data

# Normalizing the data

z = test[, c(3:14)]
means = apply(z, 2, mean)
sds = apply(z, 2, sd)
nor = scale(z, center = means, scale = sds) 

# How many clusters? 
fviz_nbclust(nor, kmeans, method = "silhouette") # 2 clusters

# K Means on 2 Clusters
kmeans_result = kmeans(nor, centers = 2)  # default gives 46.4%
kmeans_result 
## K-means clustering with 2 clusters of sizes 26, 73
## 
## Cluster means:
##      RPL_EJI EP_MINRTY  EP_POV200  EP_NOHSDP EP_RENTER  EP_HOUBDN  EPL_NOINT
## 1 -1.3227434 -1.140454 -1.2982959 -1.1084992 -1.267572 -1.1984341 -0.7823517
## 2  0.4711141  0.406189  0.4624068  0.3948079  0.451464  0.4268395  0.2786458
##    EP_ASTHMA   F_CANCER EP_DIABETES     F_HVM   EP_MHLTH
## 1 -1.0272846  0.8093874  -1.1147601 -1.154450 -1.2532845
## 2  0.3658822 -0.2882750   0.3970378  0.411174  0.4463753
## 
## Clustering vector:
## 42625 42626 42636 42639 42642 42643 42652 42662 42668 42669 42671 42673 42674 
##     1     2     2     2     2     2     2     2     2     2     2     2     2 
## 42680 42682 42687 42690 42693 42696 42698 42705 42707 42712 42717 42721 42722 
##     2     2     2     2     2     2     2     2     2     2     1     1     2 
## 42725 42727 42730 42739 42746 42747 42749 42750 42751 42753 42755 42757 42758 
##     2     2     2     2     2     2     2     2     2     2     2     2     2 
## 42759 42760 42765 42766 42767 42771 42773 42775 42776 42777 42783 42796 42798 
##     2     2     2     2     2     2     1     2     2     2     1     2     2 
## 42800 42802 42809 42813 42814 42815 42816 42820 42829 42830 42831 42833 42834 
##     1     1     2     2     1     2     1     2     2     1     1     1     1 
## 42836 42846 42847 42856 42860 42863 42866 42870 42877 42878 42881 42886 42894 
##     1     1     1     2     2     2     1     1     1     2     2     2     2 
## 42897 42901 42902 42904 42905 42909 42911 42913 42920 42921 42923 42924 42926 
##     2     2     2     2     2     2     1     2     2     2     2     2     2 
## 42927 42936 42938 42953 42955 42956 42957 42961 
##     1     1     1     1     2     2     1     1 
## 
## Within cluster sum of squares by cluster:
## [1] 258.3896 371.9127
##  (between_SS / total_SS =  46.4 %)
## 
## Available components:
## 
## [1] "cluster"      "centers"      "totss"        "withinss"     "tot.withinss"
## [6] "betweenss"    "size"         "iter"         "ifault"
# Plot of Cluster
fviz_cluster(kmeans_result, data = nor)

# Silhouette coefficient
sil = as.data.frame(silhouette(kmeans_result$cluster, dist(nor)))
mean(sil$sil_width) # 0.45 <- worse than simplistic model
## [1] 0.4541851
fviz_silhouette(silhouette(kmeans_result$cluster, dist(nor)))
##   cluster size ave.sil.width
## 1       1   26          0.27
## 2       2   73          0.52

# Adding Clusters to data set
test = test %>% 
  mutate(km.group = factor(kmeans_result$cluster, labels=c("cl1","cl2"))) 

# Summarizing the cluster groups
test %>%
  group_by(km.group) %>%
  summarise(count = n(),
            RPL_EJI = mean(RPL_EJI),
            EP_MINRTY = mean(EP_MINRTY),
            EP_POV200 = mean(EP_POV200),
            EP_NOHSDP = mean(EP_NOHSDP),
            EP_RENTER = mean(EP_RENTER),
            EP_HOUBDN = mean(EP_HOUBDN),
            EPL_NOINT = mean(EPL_NOINT),
            EP_ASTHMA = mean(EP_ASTHMA),
            F_CANCER = mean(F_CANCER),
            EP_DIABETES = mean(EP_DIABETES),
            F_HVM = mean(F_HVM),
            EP_MHLTH = mean(EP_MHLTH))
# 73% are in cluster 2 (higher ratings) <- minorities
# 27% are in cluster 1 (lower ratings) <- non-minorities

# higher across the board for everything except for the flag for cancer 

New York clustering analysis

Base Model

Training Data

eji_base_ny = eji_base[which(eji_base$COUNTY == 'New York'),]
eji_base_ny = na.omit(eji_base_ny)

# Setting seed 
set.seed(123)

train_sample = sample(seq_len(nrow(eji_base_ny)), size = 195)
train = eji_base_ny[train_sample, ]
test = eji_base_ny[-train_sample, ]

# Training data
# Normalizing the data

z = train[, c(5:7)]
means = apply(z, 2, mean)
sds = apply(z, 2, sd)
nor = scale(z, center = means, scale = sds) 

# How many clusters? 
fviz_nbclust(nor, kmeans, method = "silhouette") # 2 clusters

# K Means on 2 Clusters
kmeans_result = kmeans(nor, centers = 2)  # default gives 78.7%
kmeans_result 
## K-means clustering with 2 clusters of sizes 118, 77
## 
## Cluster means:
##   EP_MINRTY    RPL_EJI    RPL_SVM
## 1 -0.722208 -0.6998813 -0.7233572
## 2  1.106760  1.0725453  1.1085215
## 
## Clustering vector:
## 45097 44930 45113 45035 45148 45163 45200 45071 45007 45008 45176 45115 45190 
##     1     1     2     2     2     2     1     1     2     1     2     2     2 
## 45054 44942 44923 45186 45174 45129 44994 44997 44959 45061 44948 45153 45026 
##     1     2     1     2     2     2     1     1     1     1     1     2     1 
## 45184 45183 45087 44990 44939 45073 45106 44969 45052 45166 45168 45143 45084 
##     1     1     2     1     2     1     1     1     1     2     2     2     1 
## 45135 44950 45140 44985 44988 44992 44979 45059 45128 45014 45187 45192 44954 
##     2     2     2     1     1     1     1     1     1     1     1     2     1 
## 44937 45125 44957 45093 45191 44976 44932 45033 45011 44922 45118 45003 45134 
##     2     2     1     2     2     1     2     1     2     1     1     1     2 
## 44955 45077 45127 45197 44966 45158 44920 44929 45156 45044 45196 44968 44938 
##     1     1     2     1     1     2     1     1     2     1     2     1     2 
## 45006 45078 44941 44951 45086 45029 44946 45058 45131 45038 45027 45076 44980 
##     1     1     2     1     1     1     1     1     2     1     1     1     1 
## 45060 44983 45069 45039 44995 45002 45083 45053 44967 45170 45096 45023 45015 
##     1     1     1     1     1     1     2     1     1     2     2     1     1 
## 45201 45123 44933 44962 44970 45081 45109 45137 45102 44940 45030 45024 45165 
##     1     1     2     1     1     1     2     2     1     1     1     1     2 
## 45104 45072 45019 45088 45162 44921 44986 45157 45160 45189 45146 44971 44991 
##     1     1     1     1     2     2     1     2     2     2     2     1     1 
## 45000 45132 45089 45172 44964 44993 45067 45028 45066 44916 45198 45188 45108 
##     1     2     2     2     1     1     1     2     1     2     2     2     1 
## 45005 45065 44936 45021 45010 45121 45025 45120 44965 44958 44975 45001 44927 
##     1     1     1     1     1     1     1     2     1     1     2     1     1 
## 45110 45080 44924 45090 45101 45182 44982 45082 45062 45037 45074 45155 44960 
##     2     1     2     1     2     2     1     1     1     2     1     2     1 
## 45122 44952 44961 45193 45064 45004 44949 44956 45020 44926 45119 45114 44998 
##     2     1     1     2     1     1     1     2     1     1     2     2     1 
## 44925 45173 45013 44974 44977 45161 45079 45175 45111 45169 45185 45050 44973 
##     2     2     1     1     1     2     1     2     2     2     2     2     1 
## 
## Within cluster sum of squares by cluster:
## [1] 59.70005 63.69456
##  (between_SS / total_SS =  78.8 %)
## 
## Available components:
## 
## [1] "cluster"      "centers"      "totss"        "withinss"     "tot.withinss"
## [6] "betweenss"    "size"         "iter"         "ifault"
# Plot of Cluster
fviz_cluster(kmeans_result, data = nor)

# Silhouette coefficient
sil = as.data.frame(silhouette(kmeans_result$cluster, dist(nor)))
mean(sil$sil_width) # 0.66 <- could potentially have a better algorithm
## [1] 0.6641234
fviz_silhouette(silhouette(kmeans_result$cluster, dist(nor)))
##   cluster size ave.sil.width
## 1       1  118          0.70
## 2       2   77          0.61

# Adding Clusters to data set
train = train %>% 
  mutate(km.group = factor(kmeans_result$cluster, labels=c("cl1","cl2"))) 

# Summarizing the cluster groups
train %>%
  group_by(km.group) %>%
  summarise(count = n(),
            E_PM = mean(E_PM),
            RPL_EJI = mean(RPL_EJI),
            RPL_SVM = mean(RPL_SVM))
# 61% are in cluster 1 (lower ratings) <- non-minorities
# 39% are in cluster 2 (higher ratings) <- minorities 
   # same as the bronx 
   # lower E_PM but higher everything else

table(train$km.group, train$minority)
##      
##       minority non-minority
##   cl1        4          114
##   cl2       74            3
# cluster 1 has 5% of minority groups

# Are there significant differences?

aov_test = aov(RPL_EJI ~ km.group, data = train)
summary(aov_test) #yes there are significant differences 
##              Df Sum Sq Mean Sq F value Pr(>F)    
## km.group      1  7.231   7.231   593.2 <2e-16 ***
## Residuals   193  2.353   0.012                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
aov_test = aov(RPL_SVM ~ km.group, data = train)
summary(aov_test) #yes there are significant differences 
##              Df Sum Sq Mean Sq F value Pr(>F)    
## km.group      1  16.29   16.29   801.8 <2e-16 ***
## Residuals   193   3.92    0.02                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
aov_test = aov(E_PM ~ km.group, data = train)
summary(aov_test) #yes there are significant differences
##              Df Sum Sq Mean Sq F value Pr(>F)    
## km.group      1 0.4046  0.4046   98.96 <2e-16 ***
## Residuals   193 0.7890  0.0041                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Testing Data

# Setting seed 
set.seed(123)

z = test[, c(5:7)]
means = apply(z, 2, mean)
sds = apply(z, 2, sd)
nor = scale(z, center = means, scale = sds) 

# How many clusters? 
fviz_nbclust(nor, kmeans, method = "silhouette") # 2 clusters

# K Means on 2 Clusters
kmeans_result = kmeans(nor, centers = 2)  # default gives 77.2%
kmeans_result 
## K-means clustering with 2 clusters of sizes 47, 37
## 
## Cluster means:
##    EP_MINRTY    RPL_EJI    RPL_SVM
## 1 -0.7781057 -0.7833481 -0.7635081
## 2  0.9884045  0.9950638  0.9698616
## 
## Clustering vector:
## 44917 44919 44928 44931 44934 44935 44943 44944 44945 44947 44953 44963 44972 
##     2     2     2     2     1     2     2     1     1     1     1     1     1 
## 44978 44981 44984 44987 44989 44996 45009 45012 45016 45017 45018 45022 45031 
##     1     1     1     1     1     1     1     1     1     1     1     1     1 
## 45032 45034 45036 45040 45041 45042 45043 45045 45046 45047 45048 45049 45051 
##     1     1     1     1     1     1     1     1     1     1     1     1     1 
## 45055 45056 45063 45068 45070 45075 45085 45091 45092 45094 45095 45098 45099 
##     1     1     1     1     1     2     2     2     1     1     2     1     2 
## 45100 45103 45105 45107 45112 45116 45117 45124 45126 45130 45133 45136 45139 
##     1     2     2     2     1     1     2     2     1     2     2     2     2 
## 45141 45142 45144 45145 45147 45149 45150 45151 45152 45154 45159 45167 45171 
##     2     1     2     2     2     2     2     2     2     2     2     2     2 
## 45177 45178 45179 45180 45181 45195 
##     2     2     1     2     2     2 
## 
## Within cluster sum of squares by cluster:
## [1] 40.38121 16.33761
##  (between_SS / total_SS =  77.2 %)
## 
## Available components:
## 
## [1] "cluster"      "centers"      "totss"        "withinss"     "tot.withinss"
## [6] "betweenss"    "size"         "iter"         "ifault"
# Plot of Cluster
fviz_cluster(kmeans_result, data = nor)

# Silhouette coefficient
sil = as.data.frame(silhouette(kmeans_result$cluster, dist(nor)))
mean(sil$sil_width) # 0.64 <- could potentially have a better algorithm
## [1] 0.6397898
fviz_silhouette(silhouette(kmeans_result$cluster, dist(nor)))
##   cluster size ave.sil.width
## 1       1   47          0.58
## 2       2   37          0.71

# Adding Clusters to data set
test = test %>% 
  mutate(km.group = factor(kmeans_result$cluster, labels=c("cl1","cl2"))) 

# Summarizing the cluster groups
test %>%
  group_by(km.group) %>%
  summarise(count = n(),
            E_PM = mean(E_PM),
            RPL_EJI = mean(RPL_EJI),
            RPL_SVM = mean(RPL_SVM))
# 56% are in cluster 1 (higher ratings) <- non-minorities
# 44% are in cluster 2 (lower ratings) <- minorities

table(test$km.group, test$minority)
##      
##       minority non-minority
##   cl1        6           41
##   cl2       36            1
# cluster 1 has 14% of minority groups

# Are there significant differences?

aov_test = aov(RPL_EJI ~ km.group, data = test)
summary(aov_test) #yes there are significant differences 
##             Df Sum Sq Mean Sq F value Pr(>F)    
## km.group     1  3.357   3.357   306.4 <2e-16 ***
## Residuals   82  0.898   0.011                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
aov_test = aov(RPL_SVM ~ km.group, data = test)
summary(aov_test) #yes there are significant differences 
##             Df Sum Sq Mean Sq F value Pr(>F)    
## km.group     1  6.556   6.556   245.2 <2e-16 ***
## Residuals   82  2.192   0.027                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
aov_test = aov(E_PM ~ km.group, data = test)
summary(aov_test) #yes there are significant differences
##             Df Sum Sq Mean Sq F value   Pr(>F)    
## km.group     1 0.1971 0.19710   57.41 4.78e-11 ***
## Residuals   82 0.2815 0.00343                     
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

More Complex Model

Training Data

eji_base_ny = eji_ny[which(eji_ny$COUNTY == 'New York'),]
eji_base_ny = na.omit(eji_base_ny)

eji_complex_ny = eji_base_ny[, c("NAME", "COUNTY", "RPL_EJI", "EP_MINRTY", "EP_POV200",  "EP_NOHSDP", "EP_RENTER",  "EP_HOUBDN", "EPL_NOINT", "EP_ASTHMA","F_CANCER",  "EP_DIABETES",  "F_HVM",  "EP_MHLTH")]

# Setting seed 
set.seed(123)

train_sample = sample(seq_len(nrow(eji_complex_ny)), size = 231)
train = eji_complex_ny[train_sample, ]
test = eji_complex_ny[-train_sample, ]

# Training data
# Normalizing the data

z = train[, c(3:14)]
means = apply(z, 2, mean)
sds = apply(z, 2, sd)
nor = scale(z, center = means, scale = sds) 

# How many clusters? 
fviz_nbclust(nor, kmeans, method = "silhouette") # 2 clusters

# K Means on 2 Clusters
kmeans_result = kmeans(nor, centers = 2)  # default gives 57%
kmeans_result 
## K-means clustering with 2 clusters of sizes 84, 147
## 
## Cluster means:
##      RPL_EJI  EP_MINRTY  EP_POV200  EP_NOHSDP  EP_RENTER  EP_HOUBDN  EPL_NOINT
## 1  1.1393056  1.1567714  1.0987329  1.1077865  0.7677314  1.0667238  0.9755524
## 2 -0.6510318 -0.6610122 -0.6278474 -0.6330209 -0.4387037 -0.6095564 -0.5574585
##    EP_ASTHMA   F_CANCER EP_DIABETES      F_HVM   EP_MHLTH
## 1  1.0268780 -0.3304855    1.060019  0.8325441  1.0926050
## 2 -0.5867874  0.1888488   -0.605725 -0.4757395 -0.6243457
## 
## Clustering vector:
## 45097 44930 45113 45035 45148 45163 45200 45071 45007 45008 45176 45115 45190 
##     2     2     1     1     1     1     2     2     2     2     2     1     1 
## 45054 44942 44923 45186 45174 45129 44994 44997 44959 45061 44948 45153 45026 
##     2     1     2     1     1     1     2     2     2     2     2     1     2 
## 45184 45183 45087 44990 44939 45073 45106 44969 45052 45166 45168 45143 45084 
##     2     2     1     2     1     2     2     2     2     1     1     1     2 
## 45135 44950 45140 44985 44988 44992 44979 45059 45128 45014 45187 45192 44954 
##     1     1     1     2     2     2     2     2     2     2     2     1     2 
## 44937 45125 44957 45093 45191 44976 44932 45033 45011 44922 45118 45003 45134 
##     1     1     2     1     1     2     1     2     2     2     2     2     1 
## 44955 45077 45127 45197 44966 45158 44920 44929 45156 45044 45196 44968 44938 
##     2     2     1     2     2     1     2     2     1     2     1     2     1 
## 45006 45078 44941 44951 45086 45029 44946 45058 45131 45038 45027 45076 44980 
##     2     2     1     2     2     2     2     2     1     2     2     2     2 
## 45060 44983 45069 45039 44995 45002 45083 45053 44967 45170 45096 45023 45015 
##     2     2     2     2     2     2     1     2     2     1     1     2     2 
## 45201 45123 44933 44962 44970 45081 45109 45137 45102 44940 45030 45024 45165 
##     2     2     1     2     2     2     1     1     2     2     2     2     1 
## 45104 45072 45019 45088 45162 44921 44986 45157 45160 45189 45146 44971 44991 
##     2     2     2     2     2     1     2     1     1     1     1     2     2 
## 45000 45132 45089 45172 44964 44993 45067 45028 45066 44916 45198 45188 45108 
##     2     1     1     1     2     2     2     2     2     1     1     1     2 
## 45005 45065 44936 45021 45010 45121 45025 45120 44965 44958 44975 45001 44927 
##     2     2     2     2     2     2     2     1     2     2     1     2     2 
## 45110 45080 44924 45090 45101 45182 44982 45082 45062 45037 45074 45155 44960 
##     1     2     1     2     1     1     2     2     2     2     2     1     2 
## 45122 44952 44961 45193 45064 45004 44949 44956 45020 44926 45119 45114 44998 
##     1     2     2     1     2     2     2     1     2     2     1     1     2 
## 44925 45173 45013 44974 44977 45161 45079 45175 45111 45169 45185 45050 44973 
##     1     1     2     2     2     2     2     2     1     1     1     2     2 
## 44945 45018 45195 45017 45032 45041 45117 45048 45022 45012 45180 45171 45149 
##     1     2     1     2     2     2     1     2     2     2     1     1     1 
## 45036 45099 45139 45136 45112 45055 45042 45154 44943 45070 45068 45141 45094 
##     2     1     1     1     2     2     2     1     1     2     2     1     2 
## 45107 45144 45051 44984 45151 45056 44947 44981 45091 44953 
##     1     1     2     2     1     2     2     2     1     2 
## 
## Within cluster sum of squares by cluster:
## [1] 547.3105 638.7466
##  (between_SS / total_SS =  57.0 %)
## 
## Available components:
## 
## [1] "cluster"      "centers"      "totss"        "withinss"     "tot.withinss"
## [6] "betweenss"    "size"         "iter"         "ifault"
# Plot of Cluster
fviz_cluster(kmeans_result, data = nor)

# Silhouette coefficient
sil = as.data.frame(silhouette(kmeans_result$cluster, dist(nor)))
mean(sil$sil_width) # 0.49 <- worse than simplistic model
## [1] 0.4924989
fviz_silhouette(silhouette(kmeans_result$cluster, dist(nor)))
##   cluster size ave.sil.width
## 1       1   84          0.41
## 2       2  147          0.54

# Adding Clusters to data set
train = train %>% 
  mutate(km.group = factor(kmeans_result$cluster, labels=c("cl1","cl2"))) 

# Summarizing the cluster groups
train %>%
  group_by(km.group) %>%
  summarise(count = n(),
            RPL_EJI = mean(RPL_EJI),
            EP_MINRTY = mean(EP_MINRTY),
            EP_POV200 = mean(EP_POV200),
            EP_NOHSDP = mean(EP_NOHSDP),
            EP_RENTER = mean(EP_RENTER),
            EP_HOUBDN = mean(EP_HOUBDN),
            EPL_NOINT = mean(EPL_NOINT),
            EP_ASTHMA = mean(EP_ASTHMA),
            F_CANCER = mean(F_CANCER),
            EP_DIABETES = mean(EP_DIABETES),
            F_HVM = mean(F_HVM),
            EP_MHLTH = mean(EP_MHLTH))
# 37% are in cluster 1 (higher ratings) <- minorities
# 63% are in cluster 2 (lower ratings) <- non-minorities

# higher across the board for everything except for the flag for cancer 

Testing Data

# Normalizing the data

z = test[, c(3:14)]
means = apply(z, 2, mean)
sds = apply(z, 2, sd)
nor = scale(z, center = means, scale = sds) 

# How many clusters? 
fviz_nbclust(nor, kmeans, method = "silhouette") # 2 clusters

# K Means on 2 Clusters
kmeans_result = kmeans(nor, centers = 2)  # default gives 60.7%
kmeans_result 
## K-means clustering with 2 clusters of sizes 27, 21
## 
## Cluster means:
##      RPL_EJI  EP_MINRTY  EP_POV200  EP_NOHSDP  EP_RENTER  EP_HOUBDN  EPL_NOINT
## 1 -0.7811379 -0.7499181 -0.7631320 -0.7183881 -0.5144063 -0.7006776 -0.7000508
## 2  1.0043202  0.9641804  0.9811697  0.9236419  0.6613796  0.9008712  0.9000653
##    EP_ASTHMA   F_CANCER EP_DIABETES      F_HVM   EP_MHLTH
## 1 -0.6225903  0.2320532  -0.7695131 -0.6972952 -0.7120020
## 2  0.8004733 -0.2983541   0.9893740  0.8965224  0.9154311
## 
## Clustering vector:
## 44917 44919 44928 44931 44934 44935 44944 44963 44972 44978 44987 44989 44996 
##     2     2     2     2     1     2     1     1     1     1     1     1     1 
## 45009 45016 45031 45034 45040 45043 45045 45046 45047 45049 45063 45075 45085 
##     1     1     1     1     1     1     1     1     1     1     1     2     2 
## 45092 45095 45098 45100 45103 45105 45116 45124 45126 45130 45133 45142 45145 
##     1     2     1     1     2     2     1     1     1     2     2     1     2 
## 45147 45150 45152 45159 45167 45177 45178 45179 45181 
##     2     2     2     2     2     2     2     1     2 
## 
## Within cluster sum of squares by cluster:
## [1] 141.04878  80.84272
##  (between_SS / total_SS =  60.7 %)
## 
## Available components:
## 
## [1] "cluster"      "centers"      "totss"        "withinss"     "tot.withinss"
## [6] "betweenss"    "size"         "iter"         "ifault"
# Plot of Cluster
fviz_cluster(kmeans_result, data = nor)

# Silhouette coefficient
sil = as.data.frame(silhouette(kmeans_result$cluster, dist(nor)))
mean(sil$sil_width) # 0.5 <- worse than simplistic model
## [1] 0.4984769
fviz_silhouette(silhouette(kmeans_result$cluster, dist(nor)))
##   cluster size ave.sil.width
## 1       1   27          0.47
## 2       2   21          0.53

# Adding Clusters to data set
test = test %>% 
  mutate(km.group = factor(kmeans_result$cluster, labels=c("cl1","cl2"))) 

# Summarizing the cluster groups
test %>%
  group_by(km.group) %>%
  summarise(count = n(),
            RPL_EJI = mean(RPL_EJI),
            EP_MINRTY = mean(EP_MINRTY),
            EP_POV200 = mean(EP_POV200),
            EP_NOHSDP = mean(EP_NOHSDP),
            EP_RENTER = mean(EP_RENTER),
            EP_HOUBDN = mean(EP_HOUBDN),
            EPL_NOINT = mean(EPL_NOINT),
            EP_ASTHMA = mean(EP_ASTHMA),
            F_CANCER = mean(F_CANCER),
            EP_DIABETES = mean(EP_DIABETES),
            F_HVM = mean(F_HVM),
            EP_MHLTH = mean(EP_MHLTH))
# 56% are in cluster 1 (lower ratings) <- non-minorities
# 44% are in cluster 2 (higher ratings) <- minorities

# higher across the board for everything except for the flag for cancer 

Kings clustering analysis

Base Model

Training Data

eji_base_kings = eji_base[which(eji_base$COUNTY == 'Kings'),]
eji_base_kings = na.omit(eji_base_kings)

# Setting seed 
set.seed(123)

train_sample = sample(seq_len(nrow(eji_base_kings)), size = 524)
train = eji_base_kings[train_sample, ]
test = eji_base_kings[-train_sample, ]

# Training data
# Normalizing the data

z = train[, c(5:7)]
means = apply(z, 2, mean)
sds = apply(z, 2, sd)
nor = scale(z, center = means, scale = sds) 

# How many clusters? 
fviz_nbclust(nor, kmeans, method = "silhouette") # 2 clusters

# K Means on 2 Clusters
kmeans_result = kmeans(nor, centers = 2)  # default gives 50%
kmeans_result 
## K-means clustering with 2 clusters of sizes 224, 300
## 
## Cluster means:
##    EP_MINRTY   RPL_EJI    RPL_SVM
## 1 -0.7965071 -0.829350 -0.8279588
## 2  0.5947253  0.619248  0.6182092
## 
## Clustering vector:
## 44049 44097 43812 44160 43828 43749 43932 43862 43877 43643 44008 44304 44239 
##     2     2     1     1     1     1     2     1     1     2     1     2     2 
## 44240 44348 43721 43982 44287 43989 43655 44153 44060 44371 43844 44227 44230 
##     2     2     1     1     2     2     1     1     2     2     2     2     1 
## 44192 44007 43776 44179 44124 44259 43652 43942 43768 43857 43799 43850 43923 
##     2     2     2     1     1     2     1     2     1     2     2     2     2 
## 44218 43702 44225 44212 43774 43786 43927 43910 44387 43670 44065 43720 43949 
##     2     2     2     2     2     1     1     2     1     1     2     1     2 
## 43856 44162 43747 44243 44090 44235 43668 43792 43842 44378 43663 44150 43642 
##     2     2     1     2     2     2     1     2     2     2     2     1     2 
## 43699 44043 43941 43911 43719 44172 43924 44058 43919 44310 43752 43740 43791 
##     2     2     1     2     1     1     1     2     2     2     1     1     1 
## 43694 44117 44111 44114 43697 44302 43715 43798 44286 43680 43704 43811 43996 
##     2     1     1     1     2     2     2     1     2     1     2     1     2 
## 43869 44247 43963 43758 43845 43943 43876 43744 44257 44307 43784 44251 43793 
##     2     2     1     1     2     2     1     1     2     2     2     2     2 
## 44025 43788 44366 43633 43959 43913 44204 43871 43972 44329 43770 44089 44197 
##     2     1     2     1     1     2     1     1     2     1     2     1     2 
## 44226 43713 44273 43829 44314 44332 44134 43978 44290 44093 43649 44384 43797 
##     2     1     2     2     1     2     2     2     2     1     1     2     2 
## 43681 44168 43810 44191 43714 44157 44026 43935 44234 44269 44064 44062 43883 
##     2     1     1     2     2     1     1     2     2     2     1     2     1 
## 44063 44032 44334 44015 44180 43669 44156 44107 43833 43756 43898 43819 44210 
##     2     1     2     2     1     1     1     1     2     1     2     2     2 
## 43885 44092 43785 43683 44173 43868 43922 43818 44047 44236 44354 44246 43838 
##     2     2     1     2     1     2     2     1     2     2     2     2     2 
## 44317 44201 44282 44321 43980 44283 44102 44143 43686 44091 43991 43912 43903 
##     1     1     2     2     2     2     1     2     1     2     2     2     2 
## 43981 43761 43851 43970 44368 44174 44367 44190 44024 44132 43855 44055 44208 
##     1     1     2     2     2     2     2     2     1     1     2     1     1 
## 43796 44275 44324 44293 43858 44023 43748 44216 43684 44350 44388 43767 44081 
##     2     2     1     2     2     1     1     1     1     2     1     2     2 
## 43734 44362 43843 43983 44035 43891 44254 44020 44344 43653 44100 43763 44377 
##     1     2     2     2     2     2     2     2     2     1     1     2     2 
## 44011 43803 44079 43867 44056 44142 44309 43710 44308 44109 44316 43977 43956 
##     2     2     2     2     1     1     2     2     2     1     1     2     2 
## 44113 44084 43741 44205 44085 44027 43950 43928 44193 43920 44140 43703 43925 
##     1     2     1     1     1     1     2     2     2     1     1     2     2 
## 43859 44319 44012 43805 43930 44372 43723 44233 44382 44267 43870 44375 43737 
##     2     2     1     1     2     2     1     1     2     2     2     2     1 
## 43662 44268 44030 43988 44341 44327 43706 43724 44151 43659 44358 44068 43808 
##     1     2     1     1     2     1     2     1     2     1     2     2     1 
## 44326 44149 43746 44161 43971 43726 44099 43992 44385 44315 44280 44104 44199 
##     1     1     1     1     1     1     1     2     2     2     2     1     1 
## 44031 44038 43863 43781 43984 44059 44249 44057 43835 43711 44176 44105 43865 
##     1     1     2     1     1     2     2     1     2     1     1     1     2 
## 44289 43736 44009 43640 44288 43998 44167 44037 44166 43660 44048 44330 44263 
##     2     1     2     2     2     2     1     2     1     1     1     2     2 
## 44115 44088 43645 43830 44054 44297 44051 44046 44255 43641 44242 43696 43679 
##     1     2     1     2     1     2     1     2     2     1     2     2     1 
## 43837 44110 44360 44177 44018 43753 44033 44076 43948 43892 43987 43881 44223 
##     2     1     2     1     1     1     1     1     2     2     2     2     2 
## 43677 43964 43730 43738 43934 43638 44101 44277 44130 44270 44178 44272 44219 
##     1     2     1     1     2     1     1     2     1     2     1     2     2 
## 44029 44041 43636 43745 43894 43658 43939 44278 44298 43915 44137 43900 44086 
##     1     2     1     1     2     1     2     2     2     2     1     2     1 
## 43895 44352 44271 44364 43852 43817 43986 44281 43750 44262 44305 44311 44066 
##     1     2     2     2     2     1     2     2     1     2     2     2     2 
## 43665 44238 43873 43751 44228 43937 44039 44343 44042 43735 43914 43813 44071 
##     1     2     2     1     1     2     1     2     2     1     2     1     1 
## 43874 44165 43800 43676 43824 43666 43807 44374 43936 43840 43648 44294 44328 
##     2     1     2     1     1     1     2     2     2     2     1     2     1 
## 44221 43733 44380 44044 43821 43772 44127 44313 43822 43944 44200 44252 43667 
##     2     1     2     2     1     1     2     2     2     1     2     2     1 
## 44284 43952 44133 44195 44163 44002 44203 43650 43832 43717 44347 44034 44069 
##     2     2     1     2     1     2     1     1     2     2     2     1     1 
## 44357 44087 44004 44006 44188 43634 43759 43789 43921 43678 43860 43872 43826 
##     2     1     1     1     1     1     1     1     2     2     1     2     2 
## 44067 44001 44260 43823 43743 44119 44010 44072 43999 44274 43688 43690 44120 
##     2     2     2     2     1     1     1     2     2     2     2     2     1 
## 44136 44355 44131 43718 43765 44231 43884 43836 43879 43918 44338 44139 43976 
##     2     2     2     1     1     2     2     2     2     2     2     1     2 
## 43764 44122 43795 44155 43801 43708 44078 43957 43725 43854 44013 43794 44342 
##     2     1     2     1     1     2     2     1     1     2     2     2     2 
## 43875 43814 44206 44381 44017 43820 43804 43926 44215 43769 43709 43888 44022 
##     2     2     1     2     2     2     2     1     1     1     1     2     2 
## 44365 44125 44152 44126 43902 44351 43886 44073 43657 43880 44171 44108 43899 
##     2     1     1     2     2     2     1     2     1     2     1     1     2 
## 43732 43771 43739 44198 44339 44170 44202 44154 44383 43827 43908 43773 43878 
##     1     1     1     2     2     1     1     1     2     2     1     1     2 
## 43955 44292 44103 44096 
##     1     2     1     2 
## 
## Within cluster sum of squares by cluster:
## [1] 401.1490 382.3079
##  (between_SS / total_SS =  50.1 %)
## 
## Available components:
## 
## [1] "cluster"      "centers"      "totss"        "withinss"     "tot.withinss"
## [6] "betweenss"    "size"         "iter"         "ifault"
# Plot of Cluster
fviz_cluster(kmeans_result, data = nor)

# Silhouette coefficient
library(cluster)
sil = as.data.frame(silhouette(kmeans_result$cluster, dist(nor)))
mean(sil$sil_width) # 0.42 <- could potentially have a better algorithm
## [1] 0.4229785
fviz_silhouette(silhouette(kmeans_result$cluster, dist(nor)))
##   cluster size ave.sil.width
## 1       1  224          0.36
## 2       2  300          0.47

# Adding Clusters to data set
train = train %>% 
  mutate(km.group = factor(kmeans_result$cluster, labels=c("cl1","cl2"))) 

# Summarizing the cluster groups
train %>%
  group_by(km.group) %>%
  summarise(count = n(),
            E_PM = mean(E_PM),
            RPL_EJI = mean(RPL_EJI),
            RPL_SVM = mean(RPL_SVM))
# 43% are in cluster 1 (lower ratings) <- non-minorities
# 57% are in cluster 2 (higher ratings) <- minorities

table(train$km.group, train$minority)
##      
##       minority non-minority
##   cl1       31          193
##   cl2      246           54
# cluster 1 has 11% of minority groups

# Are there significant differences?

aov_test = aov(RPL_EJI ~ km.group, data = train)
summary(aov_test) #yes there are significant differences 
##              Df Sum Sq Mean Sq F value Pr(>F)    
## km.group      1  9.877   9.877   553.3 <2e-16 ***
## Residuals   522  9.318   0.018                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
aov_test = aov(RPL_SVM ~ km.group, data = train)
summary(aov_test) #yes there are significant differences 
##              Df Sum Sq Mean Sq F value Pr(>F)    
## km.group      1  14.98  14.976   549.5 <2e-16 ***
## Residuals   522  14.23   0.027                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
aov_test = aov(E_PM ~ km.group, data = train)
summary(aov_test) #yes there are significant differences
##              Df Sum Sq Mean Sq F value Pr(>F)  
## km.group      1  0.067 0.06688   4.637 0.0317 *
## Residuals   522  7.529 0.01442                 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Testing Data

# Setting seed 
set.seed(123)

z = test[, c(5:7)]
means = apply(z, 2, mean)
sds = apply(z, 2, sd)
nor = scale(z, center = means, scale = sds) 

# How many clusters? 
fviz_nbclust(nor, kmeans, method = "silhouette") # 2 clusters

# K Means on 2 Clusters
kmeans_result = kmeans(nor, centers = 2)  # default gives 51.8%
kmeans_result 
## K-means clustering with 2 clusters of sizes 79, 145
## 
## Cluster means:
##    EP_MINRTY    RPL_EJI    RPL_SVM
## 1 -0.8911325 -1.0042743 -1.0186662
## 2  0.4855136  0.5471564  0.5549974
## 
## Clustering vector:
## 43629 43630 43631 43632 43635 43637 43644 43646 43647 43651 43654 43656 43661 
##     1     2     1     1     1     1     2     1     1     1     1     1     1 
## 43664 43671 43672 43673 43674 43675 43682 43685 43687 43689 43691 43693 43695 
##     1     1     1     1     1     1     2     2     2     2     2     2     2 
## 43698 43700 43701 43705 43707 43712 43716 43722 43727 43728 43729 43731 43754 
##     2     2     2     2     2     2     2     2     1     1     1     1     1 
## 43755 43757 43766 43775 43777 43778 43779 43780 43782 43783 43787 43790 43802 
##     1     1     1     1     2     2     1     2     1     1     1     1     2 
## 43806 43809 43815 43816 43825 43831 43834 43839 43841 43846 43847 43848 43849 
##     2     2     1     2     2     2     2     2     2     2     2     2     2 
## 43853 43861 43864 43866 43882 43887 43889 43890 43893 43896 43897 43901 43904 
##     2     2     2     2     2     2     1     2     2     1     2     2     2 
## 43905 43906 43907 43909 43916 43917 43929 43931 43933 43938 43940 43945 43946 
##     2     2     1     1     2     2     2     2     2     2     2     2     2 
## 43947 43951 43953 43954 43958 43960 43961 43962 43965 43966 43967 43968 43969 
##     2     2     2     2     2     2     1     2     2     2     2     2     2 
## 43973 43975 43979 43985 43990 43993 43994 43995 43997 44000 44003 44005 44014 
##     2     1     1     2     2     2     2     2     2     2     2     2     2 
## 44016 44019 44021 44028 44036 44040 44045 44050 44052 44053 44061 44070 44074 
##     1     1     1     1     2     2     2     1     1     1     2     2     1 
## 44075 44077 44080 44082 44083 44094 44095 44098 44106 44112 44116 44118 44121 
##     2     1     2     1     2     1     1     2     1     1     1     1     2 
## 44123 44128 44129 44135 44138 44141 44144 44145 44146 44147 44148 44158 44159 
##     1     2     1     1     2     1     2     1     2     2     1     1     1 
## 44164 44175 44181 44182 44183 44184 44185 44189 44194 44196 44207 44209 44211 
##     1     2     1     1     1     1     1     2     2     1     1     1     2 
## 44213 44214 44217 44220 44222 44224 44229 44232 44237 44241 44244 44245 44248 
##     2     2     2     2     2     2     1     2     2     2     2     2     2 
## 44250 44256 44258 44261 44264 44265 44266 44276 44279 44285 44291 44295 44296 
##     2     2     2     2     2     2     2     2     2     2     2     2     2 
## 44299 44300 44303 44306 44312 44318 44320 44322 44323 44325 44331 44333 44335 
##     2     2     1     2     1     1     1     2     2     1     2     2     2 
## 44336 44337 44340 44345 44346 44349 44353 44356 44359 44361 44363 44370 44373 
##     2     2     2     2     2     2     2     2     2     2     2     2     2 
## 44376 44379 44386 
##     2     2     1 
## 
## Within cluster sum of squares by cluster:
## [1] 122.9257 199.4323
##  (between_SS / total_SS =  51.8 %)
## 
## Available components:
## 
## [1] "cluster"      "centers"      "totss"        "withinss"     "tot.withinss"
## [6] "betweenss"    "size"         "iter"         "ifault"
# Plot of Cluster
fviz_cluster(kmeans_result, data = nor)

# Silhouette coefficient
sil = as.data.frame(silhouette(kmeans_result$cluster, dist(nor)))
mean(sil$sil_width) # 0.44 <- could potentially have a better algorithm
## [1] 0.4433248
fviz_silhouette(silhouette(kmeans_result$cluster, dist(nor)))
##   cluster size ave.sil.width
## 1       1   79          0.41
## 2       2  145          0.46

# Adding Clusters to data set
test = test %>% 
  mutate(km.group = factor(kmeans_result$cluster, labels=c("cl1","cl2"))) 

# Summarizing the cluster groups
test %>%
  group_by(km.group) %>%
  summarise(count = n(),
            E_PM = mean(E_PM),
            RPL_EJI = mean(RPL_EJI),
            RPL_SVM = mean(RPL_SVM))
# 35% are in cluster 1 (higher ratings) <- non-minorities
# 65% are in cluster 2 (lower ratings) <- minorities

table(test$km.group, test$minority)
##      
##       minority non-minority
##   cl1       10           69
##   cl2      119           26
# cluster 1 has 7% of minority groups

More Complex Model

Training Data

eji_base_kings = eji_ny[which(eji_ny$COUNTY == 'Kings'),]
eji_base_kings = na.omit(eji_base_kings)

eji_complex_kings = eji_base_kings[, c("NAME", "COUNTY", "RPL_EJI", "EP_MINRTY", "EP_POV200",  "EP_NOHSDP", "EP_RENTER",  "EP_HOUBDN", "EPL_NOINT", "EP_ASTHMA","F_CANCER",  "EP_DIABETES",  "F_HVM",  "EP_MHLTH")]

# Setting seed 
set.seed(123)

train_sample = sample(seq_len(nrow(eji_complex_kings)), size = 524)
train = eji_complex_kings[train_sample, ]
test = eji_complex_kings[-train_sample, ]

# Training data
# Normalizing the data

z = train[, c(3:14)]
means = apply(z, 2, mean)
sds = apply(z, 2, sd)
nor = scale(z, center = means, scale = sds) 

# How many clusters? 
fviz_nbclust(nor, kmeans, method = "silhouette") # 2 clusters

# K Means on 2 Clusters
kmeans_result = kmeans(nor, centers = 2)  # default gives 36.9%
kmeans_result 
## K-means clustering with 2 clusters of sizes 286, 238
## 
## Cluster means:
##      RPL_EJI  EP_MINRTY  EP_POV200  EP_NOHSDP  EP_RENTER  EP_HOUBDN  EPL_NOINT
## 1 -0.6891221 -0.4011102 -0.6470383 -0.4705562 -0.4657448 -0.5984083 -0.5842828
## 2  0.8281047  0.4820064  0.7775335  0.5654583  0.5596765  0.7190956  0.7021214
##    EP_ASTHMA   F_CANCER EP_DIABETES      F_HVM   EP_MHLTH
## 1 -0.5728664  0.1511191  -0.5932903 -0.6110597 -0.6429193
## 2  0.6884025 -0.1815968   0.7129455  0.7342987  0.7725837
## 
## Clustering vector:
## 44049 44097 43812 44160 43828 43749 43932 43862 43877 43643 44008 44304 44239 
##     1     1     1     1     1     1     2     1     1     2     1     1     2 
## 44240 44348 43721 43982 44287 43989 43655 44153 44060 44371 43844 44227 44230 
##     2     2     1     1     2     2     1     1     2     1     1     2     1 
## 44192 44007 43776 44179 44124 44259 43652 43942 43768 43857 43799 43850 43923 
##     1     2     2     1     1     2     1     2     1     2     2     1     2 
## 44218 43702 44225 44212 43774 43786 43927 43910 44387 43670 44065 43720 43949 
##     1     2     2     2     1     1     1     2     1     1     2     1     2 
## 43856 44162 43747 44243 44090 44235 43668 43792 43842 44378 43663 44150 43642 
##     2     1     1     2     2     2     1     1     1     2     2     1     2 
## 43699 44043 43941 43911 43719 44172 43924 44058 43919 44310 43752 43740 43791 
##     2     1     1     2     1     1     1     2     2     1     1     1     1 
## 43694 44117 44111 44114 43697 44302 43715 43798 44286 43680 43704 43811 43996 
##     2     1     1     1     2     1     1     1     2     1     2     2     1 
## 43869 44247 43963 43758 43845 43943 43876 43744 44257 44307 43784 44251 43793 
##     1     2     1     1     2     2     1     1     2     2     1     1     2 
## 44025 43788 44366 43633 43959 43913 44204 43871 43972 44329 43770 44089 44197 
##     1     1     2     1     1     2     1     1     2     1     2     2     1 
## 44226 43713 44273 43829 44314 44332 44134 43978 44290 44093 43649 44384 43797 
##     1     1     2     2     1     2     1     2     1     1     1     2     2 
## 43681 44168 43810 44191 43714 44157 44026 43935 44234 44269 44064 44062 43883 
##     2     1     1     1     2     1     1     1     2     2     2     2     1 
## 44063 44032 44334 44015 44180 43669 44156 44107 43833 43756 43898 43819 44210 
##     2     2     2     2     1     1     1     1     2     1     2     2     1 
## 43885 44092 43785 43683 44173 43868 43922 43818 44047 44236 44354 44246 43838 
##     2     2     1     2     1     2     2     2     1     2     2     2     2 
## 44317 44201 44282 44321 43980 44283 44102 44143 43686 44091 43991 43912 43903 
##     1     1     2     1     2     2     1     1     1     1     1     2     2 
## 43981 43761 43851 43970 44368 44174 44367 44190 44024 44132 43855 44055 44208 
##     2     1     2     2     2     1     2     1     1     1     1     1     1 
## 43796 44275 44324 44293 43858 44023 43748 44216 43684 44350 44388 43767 44081 
##     2     2     1     2     1     1     1     1     1     1     1     1     2 
## 43734 44362 43843 43983 44035 43891 44254 44020 44344 43653 44100 43763 44377 
##     1     2     2     2     2     2     2     2     2     1     1     1     2 
## 44011 43803 44079 43867 44056 44142 44309 43710 44308 44109 44316 43977 43956 
##     1     2     2     2     1     1     1     2     2     1     1     1     1 
## 44113 44084 43741 44205 44085 44027 43950 43928 44193 43920 44140 43703 43925 
##     1     2     1     1     2     2     2     2     1     1     1     2     2 
## 43859 44319 44012 43805 43930 44372 43723 44233 44382 44267 43870 44375 43737 
##     2     1     1     2     2     2     1     1     2     2     2     2     1 
## 43662 44268 44030 43988 44341 44327 43706 43724 44151 43659 44358 44068 43808 
##     1     2     2     1     2     1     2     1     1     1     2     2     1 
## 44326 44149 43746 44161 43971 43726 44099 43992 44385 44315 44280 44104 44199 
##     1     1     1     1     1     1     1     1     2     1     2     1     1 
## 44031 44038 43863 43781 43984 44059 44249 44057 43835 43711 44176 44105 43865 
##     2     2     2     1     2     2     2     1     2     1     1     1     2 
## 44289 43736 44009 43640 44288 43998 44167 44037 44166 43660 44048 44330 44263 
##     2     1     2     2     2     2     1     2     1     1     1     2     2 
## 44115 44088 43645 43830 44054 44297 44051 44046 44255 43641 44242 43696 43679 
##     1     2     1     2     1     1     1     2     2     1     2     2     1 
## 43837 44110 44360 44177 44018 43753 44033 44076 43948 43892 43987 43881 44223 
##     2     1     2     1     1     1     1     1     2     2     2     2     2 
## 43677 43964 43730 43738 43934 43638 44101 44277 44130 44270 44178 44272 44219 
##     1     2     1     1     2     1     1     2     1     2     1     2     2 
## 44029 44041 43636 43745 43894 43658 43939 44278 44298 43915 44137 43900 44086 
##     2     1     1     1     1     1     2     2     1     2     1     2     1 
## 43895 44352 44271 44364 43852 43817 43986 44281 43750 44262 44305 44311 44066 
##     1     2     2     1     1     2     2     2     1     2     1     2     2 
## 43665 44238 43873 43751 44228 43937 44039 44343 44042 43735 43914 43813 44071 
##     1     1     1     1     1     2     1     2     2     1     2     2     1 
## 43874 44165 43800 43676 43824 43666 43807 44374 43936 43840 43648 44294 44328 
##     2     1     1     1     1     1     2     2     2     1     1     1     1 
## 44221 43733 44380 44044 43821 43772 44127 44313 43822 43944 44200 44252 43667 
##     2     1     2     2     2     1     1     1     2     1     1     2     1 
## 44284 43952 44133 44195 44163 44002 44203 43650 43832 43717 44347 44034 44069 
##     2     1     1     1     1     1     1     1     2     2     1     2     1 
## 44357 44087 44004 44006 44188 43634 43759 43789 43921 43678 43860 43872 43826 
##     2     2     1     1     1     1     1     1     2     2     1     1     2 
## 44067 44001 44260 43823 43743 44119 44010 44072 43999 44274 43688 43690 44120 
##     2     2     2     2     1     1     1     2     2     2     1     2     1 
## 44136 44355 44131 43718 43765 44231 43884 43836 43879 43918 44338 44139 43976 
##     1     2     1     1     1     2     2     1     1     2     2     1     2 
## 43764 44122 43795 44155 43801 43708 44078 43957 43725 43854 44013 43794 44342 
##     2     1     2     1     2     2     1     1     1     1     2     1     2 
## 43875 43814 44206 44381 44017 43820 43804 43926 44215 43769 43709 43888 44022 
##     2     2     1     2     2     2     2     1     1     1     1     2     2 
## 44365 44125 44152 44126 43902 44351 43886 44073 43657 43880 44171 44108 43899 
##     1     1     1     1     2     2     1     2     1     2     1     1     2 
## 43732 43771 43739 44198 44339 44170 44202 44154 44383 43827 43908 43773 43878 
##     1     1     1     2     2     1     1     1     2     1     1     1     1 
## 43955 44292 44103 44096 
##     1     1     1     2 
## 
## Within cluster sum of squares by cluster:
## [1] 2038.849 1918.665
##  (between_SS / total_SS =  36.9 %)
## 
## Available components:
## 
## [1] "cluster"      "centers"      "totss"        "withinss"     "tot.withinss"
## [6] "betweenss"    "size"         "iter"         "ifault"
# Plot of Cluster
fviz_cluster(kmeans_result, data = nor)

# Silhouette coefficient
sil = as.data.frame(silhouette(kmeans_result$cluster, dist(nor)))
mean(sil$sil_width) # 0.3 <- worse than simplistic model
## [1] 0.3032509
fviz_silhouette(silhouette(kmeans_result$cluster, dist(nor)))
##   cluster size ave.sil.width
## 1       1  286          0.32
## 2       2  238          0.28

# Adding Clusters to data set
train = train %>% 
  mutate(km.group = factor(kmeans_result$cluster, labels=c("cl1","cl2"))) 

# Summarizing the cluster groups
train %>%
  group_by(km.group) %>%
  summarise(count = n(),
            RPL_EJI = mean(RPL_EJI),
            EP_MINRTY = mean(EP_MINRTY),
            EP_POV200 = mean(EP_POV200),
            EP_NOHSDP = mean(EP_NOHSDP),
            EP_RENTER = mean(EP_RENTER),
            EP_HOUBDN = mean(EP_HOUBDN),
            EPL_NOINT = mean(EPL_NOINT),
            EP_ASTHMA = mean(EP_ASTHMA),
            F_CANCER = mean(F_CANCER),
            EP_DIABETES = mean(EP_DIABETES),
            F_HVM = mean(F_HVM),
            EP_MHLTH = mean(EP_MHLTH))
# 54% are in cluster 1 (higher ratings) <- non-minorities
# 46% are in cluster 2 (lower ratings) <- minorities

# higher across the board for everything (even cancer flag)

Testing Data

# Normalizing the data

z = test[, c(3:14)]
means = apply(z, 2, mean)
sds = apply(z, 2, sd)
nor = scale(z, center = means, scale = sds) 

# How many clusters? 
fviz_nbclust(nor, kmeans, method = "silhouette") # 2 clusters

# K Means on 2 Clusters
kmeans_result = kmeans(nor, centers = 2)  # default gives 37.9%
kmeans_result 
## K-means clustering with 2 clusters of sizes 114, 110
## 
## Cluster means:
##      RPL_EJI  EP_MINRTY  EP_POV200  EP_NOHSDP  EP_RENTER  EP_HOUBDN  EPL_NOINT
## 1 -0.7567783 -0.4538955 -0.7027089 -0.5087535 -0.5092228 -0.6918298 -0.6260091
## 2  0.7842975  0.4704007  0.7282620  0.5272536  0.5277400  0.7169872  0.6487731
##    EP_ASTHMA   F_CANCER EP_DIABETES      F_HVM   EP_MHLTH
## 1 -0.5982866  0.1786780  -0.6670296 -0.6043358 -0.7095166
## 2  0.6200424 -0.1851754   0.6912852  0.6263116  0.7353172
## 
## Clustering vector:
## 43629 43630 43631 43632 43635 43637 43644 43646 43647 43651 43654 43656 43661 
##     1     2     1     1     1     1     2     1     1     1     1     1     1 
## 43664 43671 43672 43673 43674 43675 43682 43685 43687 43689 43691 43693 43695 
##     1     1     1     1     1     1     2     2     2     2     2     1     2 
## 43698 43700 43701 43705 43707 43712 43716 43722 43727 43728 43729 43731 43754 
##     2     1     2     2     2     2     2     2     1     1     1     1     1 
## 43755 43757 43766 43775 43777 43778 43779 43780 43782 43783 43787 43790 43802 
##     1     1     1     1     2     2     1     2     1     1     1     1     1 
## 43806 43809 43815 43816 43825 43831 43834 43839 43841 43846 43847 43848 43849 
##     2     2     2     2     2     1     2     2     2     2     1     2     1 
## 43853 43861 43864 43866 43882 43887 43889 43890 43893 43896 43897 43901 43904 
##     2     2     1     2     2     1     1     2     1     1     2     2     2 
## 43905 43906 43907 43909 43916 43917 43929 43931 43933 43938 43940 43945 43946 
##     2     2     2     1     2     2     2     2     2     2     2     2     2 
## 43947 43951 43953 43954 43958 43960 43961 43962 43965 43966 43967 43968 43969 
##     2     2     1     2     2     1     1     2     1     2     1     2     2 
## 43973 43975 43979 43985 43990 43993 43994 43995 43997 44000 44003 44005 44014 
##     2     1     1     2     1     1     1     2     2     1     1     2     1 
## 44016 44019 44021 44028 44036 44040 44045 44050 44052 44053 44061 44070 44074 
##     1     1     1     2     1     2     1     1     1     1     2     2     1 
## 44075 44077 44080 44082 44083 44094 44095 44098 44106 44112 44116 44118 44121 
##     1     1     1     1     2     1     1     2     1     1     1     1     2 
## 44123 44128 44129 44135 44138 44141 44144 44145 44146 44147 44148 44158 44159 
##     1     1     1     1     1     1     1     1     2     2     1     1     1 
## 44164 44175 44181 44182 44183 44184 44185 44189 44194 44196 44207 44209 44211 
##     1     1     1     1     1     1     1     1     1     1     1     1     2 
## 44213 44214 44217 44220 44222 44224 44229 44232 44237 44241 44244 44245 44248 
##     2     2     1     1     2     2     1     2     2     2     2     2     1 
## 44250 44256 44258 44261 44264 44265 44266 44276 44279 44285 44291 44295 44296 
##     2     2     2     2     2     2     2     2     2     2     2     2     1 
## 44299 44300 44303 44306 44312 44318 44320 44322 44323 44325 44331 44333 44335 
##     2     1     1     1     1     1     1     1     1     1     2     2     2 
## 44336 44337 44340 44345 44346 44349 44353 44356 44359 44361 44363 44370 44373 
##     2     2     2     2     2     2     2     2     2     2     2     1     1 
## 44376 44379 44386 
##     2     2     2 
## 
## Within cluster sum of squares by cluster:
## [1] 810.0261 852.7461
##  (between_SS / total_SS =  37.9 %)
## 
## Available components:
## 
## [1] "cluster"      "centers"      "totss"        "withinss"     "tot.withinss"
## [6] "betweenss"    "size"         "iter"         "ifault"
# Plot of Cluster
fviz_cluster(kmeans_result, data = nor)

# Silhouette coefficient
sil = as.data.frame(silhouette(kmeans_result$cluster, dist(nor)))
mean(sil$sil_width) # 0.3 <- worse than simplistic model
## [1] 0.302411
fviz_silhouette(silhouette(kmeans_result$cluster, dist(nor)))
##   cluster size ave.sil.width
## 1       1  114          0.31
## 2       2  110          0.29

# Adding Clusters to data set
test = test %>% 
  mutate(km.group = factor(kmeans_result$cluster, labels=c("cl1","cl2"))) 

# Summarizing the cluster groups
test %>%
  group_by(km.group) %>%
  summarise(count = n(),
            RPL_EJI = mean(RPL_EJI),
            EP_MINRTY = mean(EP_MINRTY),
            EP_POV200 = mean(EP_POV200),
            EP_NOHSDP = mean(EP_NOHSDP),
            EP_RENTER = mean(EP_RENTER),
            EP_HOUBDN = mean(EP_HOUBDN),
            EPL_NOINT = mean(EPL_NOINT),
            EP_ASTHMA = mean(EP_ASTHMA),
            F_CANCER = mean(F_CANCER),
            EP_DIABETES = mean(EP_DIABETES),
            F_HVM = mean(F_HVM),
            EP_MHLTH = mean(EP_MHLTH))
# 51% are in cluster 1 (lower ratings) <- non-minorities
# 49% are in cluster 2 (higher ratings) <- minorities

# higher across the board for everything except for the flag for cancer 

Queens clustering analysis

Base Model

Training Data

eji_base_queens = eji_base[which(eji_base$COUNTY == 'Queens'),]
eji_base_queens = na.omit(eji_base_queens)

# Setting seed 
set.seed(123)

train_sample = sample(seq_len(nrow(eji_base_queens)), size = 449)
train = eji_base_queens[train_sample, ]
test = eji_base_queens[-train_sample, ]

# Training data
# Normalizing the data

z = train[, c(5:7)]
means = apply(z, 2, mean)
sds = apply(z, 2, sd)
nor = scale(z, center = means, scale = sds) 

# How many clusters? 
fviz_nbclust(nor, kmeans, method = "silhouette") # 2 clusters

# K Means on 2 Clusters
kmeans_result = kmeans(nor, centers = 2)  # default gives 50.5%
kmeans_result 
## K-means clustering with 2 clusters of sizes 195, 254
## 
## Cluster means:
##    EP_MINRTY    RPL_EJI    RPL_SVM
## 1 -0.8155717 -0.8446015 -0.7692942
## 2  0.6261279  0.6484146  0.5905999
## 
## Clustering vector:
## 46087 46138 45843 46204 45859 45778 45968 45895 45910 45670 46043 46284 46285 
##     1     1     2     1     2     2     2     2     2     2     1     1     1 
## 45751 46017 46024 45683 46197 46100 45875 46271 46274 46234 46042 45804 46222 
##     2     2     2     2     2     1     2     1     2     2     2     2     2 
## 46166 45679 45978 45796 45890 45829 45882 45959 46261 45731 46268 46255 45802 
##     1     2     2     1     2     2     2     2     2     2     2     2     1 
## 45814 45963 45946 46323 45699 46105 45750 45985 45888 46206 45776 46131 45697 
##     2     2     1     1     1     1     2     2     2     2     2     1     1 
## 45820 45873 46314 45692 46194 45669 45728 46081 45977 45947 45749 46215 45960 
##     1     2     1     2     1     1     1     2     2     2     1     1     2 
## 46098 45955 45781 45770 45819 45722 46158 46152 46155 45726 45745 45828 45709 
##     1     2     2     2     2     1     2     1     1     1     1     2     1 
## 45734 45842 46031 45902 45999 45787 45876 45979 45909 45773 46249 45812 45822 
##     2     2     2     2     2     2     1     2     2     2     1     2     1 
## 46060 45816 46306 45661 45995 45949 45904 46008 46304 45798 46130 45743 46220 
##     1     2     2     1     1     2     2     1     1     1     1     1     1 
## 45860 46286 46176 46013 46235 46134 45676 46320 45827 45710 45841 45744 46201 
##     2     1     2     2     1     1     2     1     2     1     2     2     1 
## 46061 45971 46104 46102 45918 46103 46069 46050 45698 46148 45864 45785 46177 
##     1     2     2     1     2     1     2     1     1     1     1     2     2 
## 45934 45931 46229 45850 45719 45920 46133 45813 45988 45712 46079 46308 45901 
##     2     2     1     2     2     2     1     2     2     1     2     1     2 
## 45958 45849 45921 46085 45775 45666 46296 46178 45869 46032 45936 45682 46303 
##     2     2     1     1     1     1     1     2     2     2     2     2     1 
## 45951 46185 46262 45880 46015 46230 46143 46080 45715 46132 45765 46026 45948 
##     2     2     2     2     2     2     1     2     1     1     2     2     2 
## 45939 46035 45795 46016 45790 45883 45766 46038 46184 46006 45954 46213 45684 
##     2     2     1     1     2     1     1     1     2     1     2     1     2 
## 45663 46118 45911 45815 46279 46236 46059 45887 46269 46018 45806 46122 46094 
##     2     1     2     2     1     1     1     2     2     2     1     1     1 
## 46232 45809 45826 46299 45823 45725 45660 46239 45891 46058 45777 46163 45797 
##     1     2     2     1     1     2     2     1     2     1     1     2     2 
## 45713 46291 46246 45703 45807 45834 46324 46145 45863 46030 45840 46072 46151 
##     2     2     1     1     2     2     2     1     2     1     2     1     1 
## 46168 45764 46093 46179 46099 45874 46124 46095 46112 45926 46205 46055 46312 
##     2     1     2     2     1     2     1     2     2     2     1     2     1 
## 45680 45791 46245 45855 45736 46046 45938 46199 45862 46241 45900 46037 46251 
##     2     2     1     2     2     1     2     1     2     2     2     1     2 
## 45740 45694 46257 46172 46012 45992 45706 45771 46193 45986 45964 46126 45956 
##     2     1     2     2     2     1     1     1     2     2     2     1     2 
## 46052 45733 45961 45892 46260 45836 45966 46310 45753 46189 46318 46216 45903 
##     1     2     2     2     2     2     2     1     1     2     1     2     2 
## 46076 45767 45690 46217 46023 46282 46287 46074 45754 46202 45687 46106 45839 
##     1     1     2     1     2     1     1     1     2     1     2     1     2 
## 46111 46170 46007 45756 46071 46021 46136 45896 46119 45866 45741 46022 45898 
##     2     1     2     1     2     1     1     2     1     2     1     2     2 
## 46302 46141 45667 46233 46153 45688 46033 46073 46029 46156 45672 45861 46242 
##     2     2     2     1     1     2     1     1     2     1     2     2     1 
## 46082 45668 46115 45708 45868 46025 46227 45782 45984 45927 45916 46174 46057 
##     1     1     2     1     2     2     2     2     1     2     2     2     1 
## 45760 45768 45970 46169 46020 46224 46196 46219 45990 45664 45774 45929 45686 
##     1     2     2     2     2     1     1     1     1     2     2     2     2 
## 46243 46161 46049 46164 45930 46294 45994 46305 45884 45848 46228 45779 46247 
##     1     2     2     2     2     1     2     1     2     2     1     2     1 
## 46253 46309 46063 46107 45906 45780 45982 46313 46276 46150 45844 46004 45907 
##     2     1     1     1     2     1     1     1     1     1     2     2     2 
## 46188 45830 45705 46075 45695 45838 46167 45871 45675 46190 46125 45942 45763 
##     1     2     1     1     2     2     2     2     2     1     1     2     2 
## 46316 46054 45852 45800 46252 45853 45989 46120 45786 45696 46321 45721 45941 
##     1     1     2     2     2     2     2     1     1     1     1     2     2 
## 45738 45729 46307 46078 46137 45937 45735 45677 46173 46088 45747 46288 45717 
##     2     2     1     1     1     2     1     2     2     2     1     1     1 
## 46002 46066 46014 46051 45987 45831 45662 45789 46056 45817 45689 45707 45885 
##     2     1     2     1     1     1     2     2     1     2     1     1     2 
## 45922 45857 46000 45867 45944 46144 46089 45854 45772 45943 46142 46048 46005 
##     2     2     1     2     2     1     1     2     2     2     2     1     1 
## 45953 45877 45905 45893 46295 46183 46292 46289 45957 46110 46297 45965 45825 
##     2     1     2     2     1     2     1     1     2     2     1     2     1 
## 45748 45793 45846 45818 46139 46283 46322 
##     2     2     2     2     1     1     1 
## 
## Within cluster sum of squares by cluster:
## [1] 367.9419 296.8786
##  (between_SS / total_SS =  50.5 %)
## 
## Available components:
## 
## [1] "cluster"      "centers"      "totss"        "withinss"     "tot.withinss"
## [6] "betweenss"    "size"         "iter"         "ifault"
# Plot of Cluster
fviz_cluster(kmeans_result, data = nor)

# Silhouette coefficient
library(cluster)
sil = as.data.frame(silhouette(kmeans_result$cluster, dist(nor)))
mean(sil$sil_width) # 0.43 <- could potentially have a better algorithm
## [1] 0.4277348
fviz_silhouette(silhouette(kmeans_result$cluster, dist(nor)))
##   cluster size ave.sil.width
## 1       1  195          0.34
## 2       2  254          0.49

# Adding Clusters to data set
train = train %>% 
  mutate(km.group = factor(kmeans_result$cluster, labels=c("cl1","cl2"))) 

# Summarizing the cluster groups
train %>%
  group_by(km.group) %>%
  summarise(count = n(),
            E_PM = mean(E_PM),
            RPL_EJI = mean(RPL_EJI),
            RPL_SVM = mean(RPL_SVM))
# 43% are in cluster 1 (lower ratings) <- non-minorities
# 57% are in cluster 2 (higher ratings) <- minorities

table(train$km.group, train$minority)
##      
##       minority non-minority
##   cl1       35          160
##   cl2      230           24
# cluster 1 has 13% of minority groups

Testing Data

# Setting seed 
set.seed(123)

z = test[, c(5:7)]
means = apply(z, 2, mean)
sds = apply(z, 2, sd)
nor = scale(z, center = means, scale = sds) 

# How many clusters? 
fviz_nbclust(nor, kmeans, method = "silhouette") # 2 clusters

# K Means on 2 Clusters
kmeans_result = kmeans(nor, centers = 2)  # default gives 49%
kmeans_result 
## K-means clustering with 2 clusters of sizes 81, 111
## 
## Cluster means:
##    EP_MINRTY    RPL_EJI    RPL_SVM
## 1 -0.6860400 -0.8714353 -0.8799832
## 2  0.5006238  0.6359122  0.6421499
## 
## Clustering vector:
## 45657 45658 45659 45665 45671 45673 45674 45678 45685 45693 45700 45701 45702 
##     1     2     2     2     2     2     2     1     2     2     1     1     2 
## 45704 45711 45714 45716 45718 45720 45723 45727 45730 45737 45739 45742 45746 
##     1     2     2     2     1     1     2     2     1     1     1     2     2 
## 45752 45755 45757 45758 45759 45761 45762 45769 45783 45784 45792 45794 45799 
##     2     2     1     1     2     2     2     1     2     2     2     2     2 
## 45801 45803 45805 45808 45810 45811 45832 45835 45837 45845 45847 45851 45856 
##     1     2     2     2     2     2     2     2     1     2     2     2     2 
## 45858 45865 45870 45872 45879 45881 45886 45894 45897 45899 45908 45912 45915 
##     1     2     2     2     2     2     1     2     2     2     2     2     2 
## 45917 45919 45923 45924 45925 45928 45933 45935 45940 45945 45950 45952 45962 
##     1     1     2     2     2     2     2     1     2     2     2     1     2 
## 45967 45969 45972 45973 45974 45975 45976 45980 45981 45983 45991 45993 45996 
##     2     1     2     2     2     2     1     2     2     1     2     2     2 
## 45997 45998 46001 46003 46009 46010 46011 46019 46027 46028 46034 46036 46039 
##     1     1     2     1     1     1     2     2     2     1     1     2     2 
## 46040 46041 46044 46045 46047 46053 46064 46065 46068 46070 46083 46084 46086 
##     2     1     2     1     1     1     1     1     1     1     1     1     1 
## 46090 46092 46097 46101 46108 46109 46113 46114 46116 46117 46121 46123 46127 
##     1     1     1     2     1     1     2     1     2     2     1     1     1 
## 46128 46135 46140 46146 46147 46149 46154 46157 46159 46162 46165 46171 46175 
##     1     1     1     1     1     1     1     2     2     2     2     2     2 
## 46180 46181 46182 46186 46187 46195 46198 46200 46203 46207 46208 46209 46210 
##     2     2     2     1     2     2     1     2     2     2     2     2     2 
## 46211 46212 46214 46218 46221 46225 46226 46231 46238 46240 46244 46248 46250 
##     2     1     1     1     2     2     2     2     1     1     1     1     2 
## 46254 46256 46258 46259 46263 46264 46265 46266 46267 46272 46273 46275 46277 
##     2     2     1     2     2     1     2     2     2     1     1     1     2 
## 46278 46280 46290 46298 46300 46301 46311 46315 46317 46319 
##     1     1     1     1     1     1     1     1     2     1 
## 
## Within cluster sum of squares by cluster:
## [1] 175.0552 117.1092
##  (between_SS / total_SS =  49.0 %)
## 
## Available components:
## 
## [1] "cluster"      "centers"      "totss"        "withinss"     "tot.withinss"
## [6] "betweenss"    "size"         "iter"         "ifault"
# Plot of Cluster
fviz_cluster(kmeans_result, data = nor)

# Silhouette coefficient
sil = as.data.frame(silhouette(kmeans_result$cluster, dist(nor)))
mean(sil$sil_width) # 0.43 <- could potentially have a better algorithm
## [1] 0.4297789
# all of cluster 1 remains under the average and has some negative values

fviz_silhouette(silhouette(kmeans_result$cluster, dist(nor)))
##   cluster size ave.sil.width
## 1       1   81          0.30
## 2       2  111          0.53

# Adding Clusters to data set
test = test %>% 
  mutate(km.group = factor(kmeans_result$cluster, labels=c("cl1","cl2"))) 

# Summarizing the cluster groups
test %>%
  group_by(km.group) %>%
  summarise(count = n(),
            E_PM = mean(E_PM),
            RPL_EJI = mean(RPL_EJI),
            RPL_SVM = mean(RPL_SVM))
# 42% are in cluster 1 (higher ratings) <- non-minorities
# 58% are in cluster 2 (lower ratings) <- minorities

table(test$km.group, test$minority)
##      
##       minority non-minority
##   cl1       21           60
##   cl2       95           16
# cluster 1 has 18% of minority groups

More Complex Model

Training Data

eji_base_queens = eji_ny[which(eji_ny$COUNTY == 'Queens'),]
eji_base_queens = na.omit(eji_base_queens)

eji_complex_queens = eji_base_queens[, c("NAME", "COUNTY", "RPL_EJI", "EP_MINRTY", "EP_POV200",  "EP_NOHSDP", "EP_RENTER",  "EP_HOUBDN", "EPL_NOINT", "EP_ASTHMA","F_CANCER",  "EP_DIABETES",  "F_HVM",  "EP_MHLTH")]

# Setting seed 
set.seed(123)

train_sample = sample(seq_len(nrow(eji_complex_queens)), size = 449)
train = eji_complex_queens[train_sample, ]
test = eji_complex_queens[-train_sample, ]

# Training data
# Normalizing the data

z = train[, c(3:14)]
means = apply(z, 2, mean)
sds = apply(z, 2, sd)
nor = scale(z, center = means, scale = sds) 

# How many clusters? 
fviz_nbclust(nor, kmeans, method = "silhouette") # 5 clusters

# K Means on 2 Clusters
kmeans_result = kmeans(nor, centers = 4)  # default gives 56.5%
kmeans_result 
## K-means clustering with 4 clusters of sizes 116, 83, 65, 185
## 
## Cluster means:
##      RPL_EJI  EP_MINRTY  EP_POV200  EP_NOHSDP  EP_RENTER   EP_HOUBDN  EPL_NOINT
## 1  0.9585426  0.6739372  1.2846043  1.0671806  0.7768907  1.10717406  0.8023883
## 2  0.3826889  0.9669762 -0.5676920 -0.2772783 -0.9475415 -0.47545063 -0.0217133
## 3 -1.3581753 -1.2130288 -1.0217715 -0.9873321 -0.9310985 -1.18957595 -0.6217621
## 4 -0.2955282 -0.4302101 -0.1917866 -0.1978501  0.2651244 -0.06295866 -0.2749205
##    EP_ASTHMA   F_CANCER EP_DIABETES      F_HVM   EP_MHLTH
## 1  0.1713256 -0.1799775   0.8820886  0.3750610  0.8564244
## 2  1.4249872 -0.3037293   0.7073637  1.3778081  0.4336809
## 3 -0.7881922  1.5182777  -0.7219856 -0.3270108 -1.3258806
## 4 -0.4698119 -0.2843304  -0.6167805 -0.7384294 -0.2657216
## 
## Clustering vector:
## 46087 46138 45843 46204 45859 45778 45968 45895 45910 45670 46043 46284 46285 
##     3     3     4     4     1     2     4     1     1     4     4     3     3 
## 45751 46017 46024 45683 46197 46100 45875 46271 46274 46234 46042 45804 46222 
##     1     2     1     1     4     3     2     4     1     4     2     4     1 
## 46166 45679 45978 45796 45890 45829 45882 45959 46261 45731 46268 46255 45802 
##     4     1     4     4     2     1     4     1     4     1     1     1     4 
## 45814 45963 45946 46323 45699 46105 45750 45985 45888 46206 45776 46131 45697 
##     1     1     4     3     4     3     4     4     2     4     4     4     4 
## 45820 45873 46314 45692 46194 45669 45728 46081 45977 45947 45749 46215 45960 
##     4     1     3     1     3     4     4     4     4     3     4     3     4 
## 46098 45955 45781 45770 45819 45722 46158 46152 46155 45726 45745 45828 45709 
##     4     1     4     2     1     4     2     4     4     4     4     1     4 
## 45734 45842 46031 45902 45999 45787 45876 45979 45909 45773 46249 45812 45822 
##     2     2     4     1     2     2     4     4     2     4     4     1     4 
## 46060 45816 46306 45661 45995 45949 45904 46008 46304 45798 46130 45743 46220 
##     4     1     3     3     4     1     1     2     4     4     4     4     3 
## 45860 46286 46176 46013 46235 46134 45676 46320 45827 45710 45841 45744 46201 
##     2     3     1     1     3     3     4     3     1     4     4     1     4 
## 46061 45971 46104 46102 45918 46103 46069 46050 45698 46148 45864 45785 46177 
##     2     1     2     3     1     3     2     4     4     3     2     2     1 
## 45934 45931 46229 45850 45719 45920 46133 45813 45988 45712 46079 46308 45901 
##     2     2     3     1     1     1     4     2     2     4     2     4     1 
## 45958 45849 45921 46085 45775 45666 46296 46178 45869 46032 45936 45682 46303 
##     4     4     2     3     4     4     3     1     1     4     1     4     4 
## 45951 46185 46262 45880 46015 46230 46143 46080 45715 46132 45765 46026 45948 
##     4     1     1     1     2     1     3     4     4     4     1     4     1 
## 45939 46035 45795 46016 45790 45883 45766 46038 46184 46006 45954 46213 45684 
##     2     1     4     4     2     4     4     4     1     4     1     4     4 
## 45663 46118 45911 45815 46279 46236 46059 45887 46269 46018 45806 46122 46094 
##     4     4     1     4     4     3     4     4     4     2     4     3     2 
## 46232 45809 45826 46299 45823 45725 45660 46239 45891 46058 45777 46163 45797 
##     4     2     4     4     4     2     4     3     2     2     4     1     2 
## 45713 46291 46246 45703 45807 45834 46324 46145 45863 46030 45840 46072 46151 
##     4     4     4     4     2     4     4     3     1     4     4     4     4 
## 46168 45764 46093 46179 46099 45874 46124 46095 46112 45926 46205 46055 46312 
##     2     4     2     1     3     4     3     2     2     1     4     2     3 
## 45680 45791 46245 45855 45736 46046 45938 46199 45862 46241 45900 46037 46251 
##     4     2     3     1     1     4     1     4     1     4     1     2     1 
## 45740 45694 46257 46172 46012 45992 45706 45771 46193 45986 45964 46126 45956 
##     4     4     4     1     2     4     4     4     1     1     1     3     1 
## 46052 45733 45961 45892 46260 45836 45966 46310 45753 46189 46318 46216 45903 
##     4     1     1     4     1     4     4     3     4     4     3     1     2 
## 46076 45767 45690 46217 46023 46282 46287 46074 45754 46202 45687 46106 45839 
##     4     4     1     3     4     3     3     4     4     4     1     4     1 
## 46111 46170 46007 45756 46071 46021 46136 45896 46119 45866 45741 46022 45898 
##     2     4     2     3     2     2     3     2     4     2     4     1     1 
## 46302 46141 45667 46233 46153 45688 46033 46073 46029 46156 45672 45861 46242 
##     4     4     4     4     3     1     4     2     4     1     1     1     3 
## 46082 45668 46115 45708 45868 46025 46227 45782 45984 45927 45916 46174 46057 
##     2     3     2     4     2     1     1     1     4     1     2     1     4 
## 45760 45768 45970 46169 46020 46224 46196 46219 45990 45664 45774 45929 45686 
##     4     1     2     1     4     4     3     3     4     4     1     1     1 
## 46243 46161 46049 46164 45930 46294 45994 46305 45884 45848 46228 45779 46247 
##     4     1     2     1     1     3     2     4     2     1     3     2     3 
## 46253 46309 46063 46107 45906 45780 45982 46313 46276 46150 45844 46004 45907 
##     1     3     2     3     2     4     4     3     4     3     1     2     1 
## 46188 45830 45705 46075 45695 45838 46167 45871 45675 46190 46125 45942 45763 
##     3     1     4     2     4     4     2     2     1     3     3     1     1 
## 46316 46054 45852 45800 46252 45853 45989 46120 45786 45696 46321 45721 45941 
##     3     4     4     2     1     1     2     4     4     4     3     4     1 
## 45738 45729 46307 46078 46137 45937 45735 45677 46173 46088 45747 46288 45717 
##     1     2     4     4     3     1     4     4     4     2     4     3     4 
## 46002 46066 46014 46051 45987 45831 45662 45789 46056 45817 45689 45707 45885 
##     2     4     2     2     2     4     4     2     2     2     3     4     4 
## 45922 45857 46000 45867 45944 46144 46089 45854 45772 45943 46142 46048 46005 
##     1     1     4     4     1     3     4     2     1     1     4     4     2 
## 45953 45877 45905 45893 46295 46183 46292 46289 45957 46110 46297 45965 45825 
##     4     4     2     1     3     1     4     4     1     1     4     1     4 
## 45748 45793 45846 45818 46139 46283 46322 
##     4     1     2     1     3     3     4 
## 
## Within cluster sum of squares by cluster:
## [1] 914.9091 336.2349 509.8658 841.5435
##  (between_SS / total_SS =  51.6 %)
## 
## Available components:
## 
## [1] "cluster"      "centers"      "totss"        "withinss"     "tot.withinss"
## [6] "betweenss"    "size"         "iter"         "ifault"
# Plot of Cluster
fviz_cluster(kmeans_result, data = nor)

# Silhouette coefficient
sil = as.data.frame(silhouette(kmeans_result$cluster, dist(nor)))
mean(sil$sil_width) # 0.24 <- worse than simplistic model
## [1] 0.2616579
fviz_silhouette(silhouette(kmeans_result$cluster, dist(nor)))
##   cluster size ave.sil.width
## 1       1  116          0.17
## 2       2   83          0.39
## 3       3   65          0.17
## 4       4  185          0.30

# Adding Clusters to data set
train = train %>% 
  mutate(km.group = factor(kmeans_result$cluster, labels=c("cl1","cl2", "cl3", "cl4"))) 

# Summarizing the cluster groups
train %>%
  group_by(km.group) %>%
  summarise(count = n(),
            RPL_EJI = mean(RPL_EJI),
            EP_MINRTY = mean(EP_MINRTY),
            EP_POV200 = mean(EP_POV200),
            EP_NOHSDP = mean(EP_NOHSDP),
            EP_RENTER = mean(EP_RENTER),
            EP_HOUBDN = mean(EP_HOUBDN),
            EPL_NOINT = mean(EPL_NOINT),
            EP_ASTHMA = mean(EP_ASTHMA),
            F_CANCER = mean(F_CANCER),
            EP_DIABETES = mean(EP_DIABETES),
            F_HVM = mean(F_HVM),
            EP_MHLTH = mean(EP_MHLTH))
# 24% are in cluster 1 (minority
# 9% are in cluster 2 (minority) (always the highest except for cancer)
# 14% are in cluster 3 (non-minority) (usually always the lowest except for cancer)
# 34% are in cluster 4 (non-minority)
# 18% are in cluster 5 (minority)

Testing Data

set.seed(123)

# Normalizing the data

z = test[, c(3:14)]
means = apply(z, 2, mean)
sds = apply(z, 2, sd)
nor = scale(z, center = means, scale = sds) 

# K Means on 2 Clusters
kmeans_result = kmeans(nor, centers = 5)  # default gives 58.8%
kmeans_result 
## K-means clustering with 5 clusters of sizes 11, 46, 64, 17, 54
## 
## Cluster means:
##      RPL_EJI  EP_MINRTY  EP_POV200  EP_NOHSDP   EP_RENTER  EP_HOUBDN  EPL_NOINT
## 1 -0.2574120 -1.8364588 -0.9960216 -0.7255288 -1.13149693 -1.2194227  0.1328327
## 2  0.3127388  0.9347425 -0.5150598 -0.2802437 -0.81919858 -0.4990581 -0.2143644
## 3 -0.8840681 -0.8373478 -0.5323650 -0.6602677  0.02537434 -0.3829706 -0.4649126
## 4  1.1258262  0.7804925  1.9174499  2.0349300  1.32350372  1.1891497  1.4758598
## 5  0.4793863  0.3245329  0.6689573  0.5284325  0.48159407  0.7530536  0.2419333
##    EP_ASTHMA  F_CANCER EP_DIABETES      F_HVM   EP_MHLTH
## 1 -0.3701351  4.045843  -0.3855915  0.5780900 -0.9403298
## 2  1.2485007 -0.245880   0.6793250  1.1703626  0.3798626
## 3 -0.6925170 -0.245880  -0.9097650 -0.8312405 -0.7183850
## 4  0.6376373 -0.245880   1.2254617  0.6397292  1.6314760
## 5 -0.3681165 -0.245880   0.1923086 -0.3309569  0.2057684
## 
## Clustering vector:
## 45657 45658 45659 45665 45671 45673 45674 45678 45685 45693 45700 45701 45702 
##     3     5     5     5     5     5     5     3     5     5     3     1     5 
## 45704 45711 45714 45716 45718 45720 45723 45727 45730 45737 45739 45742 45746 
##     3     5     5     4     3     3     4     5     5     3     3     5     5 
## 45752 45755 45757 45758 45759 45761 45762 45769 45783 45784 45792 45794 45799 
##     3     5     3     3     3     5     5     3     2     2     2     2     2 
## 45801 45803 45805 45808 45810 45811 45832 45835 45837 45845 45847 45851 45856 
##     3     2     2     2     2     2     3     5     3     5     5     5     2 
## 45858 45865 45870 45872 45879 45881 45886 45894 45897 45899 45908 45912 45915 
##     2     3     3     5     2     5     2     5     5     2     4     4     2 
## 45917 45919 45923 45924 45925 45928 45933 45935 45940 45945 45950 45952 45962 
##     2     2     2     4     4     4     4     2     4     5     3     3     5 
## 45967 45969 45972 45973 45974 45975 45976 45980 45981 45983 45991 45993 45996 
##     5     3     2     5     2     5     3     3     3     2     2     2     2 
## 45997 45998 46001 46003 46009 46010 46011 46019 46027 46028 46034 46036 46039 
##     3     3     2     3     2     3     2     5     5     2     3     5     2 
## 46040 46041 46044 46045 46047 46053 46064 46065 46068 46070 46083 46084 46086 
##     3     3     2     3     3     2     2     2     2     2     2     3     3 
## 46090 46092 46097 46101 46108 46109 46113 46114 46116 46117 46121 46123 46127 
##     1     3     2     2     1     1     5     3     5     2     3     3     3 
## 46128 46135 46140 46146 46147 46149 46154 46157 46159 46162 46165 46171 46175 
##     3     3     3     3     3     3     3     2     2     4     5     2     4 
## 46180 46181 46182 46186 46187 46195 46198 46200 46203 46207 46208 46209 46210 
##     5     5     5     1     5     5     1     1     5     5     2     4     4 
## 46211 46212 46214 46218 46221 46225 46226 46231 46238 46240 46244 46248 46250 
##     4     1     3     1     2     5     4     5     3     3     3     3     5 
## 46254 46256 46258 46259 46263 46264 46265 46266 46267 46272 46273 46275 46277 
##     4     5     3     5     5     3     5     5     5     3     3     3     5 
## 46278 46280 46290 46298 46300 46301 46311 46315 46317 46319 
##     3     3     3     3     3     3     1     1     4     3 
## 
## Within cluster sum of squares by cluster:
## [1]  71.65958 206.44037 307.73531 145.82141 213.53876
##  (between_SS / total_SS =  58.8 %)
## 
## Available components:
## 
## [1] "cluster"      "centers"      "totss"        "withinss"     "tot.withinss"
## [6] "betweenss"    "size"         "iter"         "ifault"
# Plot of Cluster
fviz_cluster(kmeans_result, data = nor)

# Silhouette coefficient
sil = as.data.frame(silhouette(kmeans_result$cluster, dist(nor)))
mean(sil$sil_width) # 0.26 <- worse than simplistic model
## [1] 0.2613641
fviz_silhouette(silhouette(kmeans_result$cluster, dist(nor)))
##   cluster size ave.sil.width
## 1       1   11          0.41
## 2       2   46          0.30
## 3       3   64          0.26
## 4       4   17          0.11
## 5       5   54          0.25

# Adding Clusters to data set
test = test %>% 
  mutate(km.group = factor(kmeans_result$cluster, labels=c("cl1","cl2", "cl3", "cl4", "cl5"))) 

# Summarizing the cluster groups
test %>%
  group_by(km.group) %>%
  summarise(count = n(),
            RPL_EJI = mean(RPL_EJI),
            EP_MINRTY = mean(EP_MINRTY),
            EP_POV200 = mean(EP_POV200),
            EP_NOHSDP = mean(EP_NOHSDP),
            EP_RENTER = mean(EP_RENTER),
            EP_HOUBDN = mean(EP_HOUBDN),
            EPL_NOINT = mean(EPL_NOINT),
            EP_ASTHMA = mean(EP_ASTHMA),
            F_CANCER = mean(F_CANCER),
            EP_DIABETES = mean(EP_DIABETES),
            F_HVM = mean(F_HVM),
            EP_MHLTH = mean(EP_MHLTH))
# 6% are in cluster 1 (non-minority)
# 24% are in cluster 2 (minority) 
# 33% are in cluster 3 (non-minority) 
# 9% are in cluster 4 (minority) (almost always the highest except for cancer)
# 28% are in cluster 5 (minority)